feat(sdk, docs): expose agent_custom_instructions for agent-scoped extraction (#6809)

docs/api-reference/organizations-projects.mdx

@@ -95,6 +95,12 @@ client.project.update(
     custom_instructions="..."
 )
 
+# Separate extraction instructions for agent-scoped memories
+# (see /platform/features/custom-instructions)
+client.project.update(
+    agent_custom_instructions="..."
+)
+
 # Use the input language for memory storage and retrieval
 client.project.update(multilingual=True)
 

docs/changelog/sdk.mdx

@@ -7,6 +7,13 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">
 
+<Update label="2026-08-05" description="v2.0.17">
+
+**New Features:**
+- **Client:** Add `agent_custom_instructions` to `project.update()`/`update_project()` (sync and async) and to the `ProjectUpdateOptions` and `AddMemoryOptions` typed models. It sets a second extraction instruction set that applies only to agent-scoped memories: an add passing `agent_id` without `user_id` uses it, one passing both splits by attribution, and while it is unset `custom_instructions` continues to apply to every memory ([#6809](https://github.com/mem0ai/mem0/pull/6809))
+
+</Update>
+
 <Update label="2026-08-04" description="v2.0.16">
 
 **New Features:**
@@ -1189,6 +1196,13 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
 
 <Tab title="TypeScript">
 
+<Update label="2026-08-05" description="v3.1.5">
+
+**New Features:**
+- **Client:** Add `agentCustomInstructions` to `PromptUpdatePayload`, `AddMemoryOptions`, and `ProjectResponse`. It sets a second extraction instruction set that applies only to agent-scoped memories: an add passing `agentId` without `userId` uses it, one passing both splits by attribution, and while it is unset `customInstructions` continues to apply to every memory ([#6809](https://github.com/mem0ai/mem0/pull/6809))
+
+</Update>
+
 <Update label="2026-08-04" description="v3.1.4">
 
 **New Features:**

docs/components/vectordbs/dbs/oracledb.mdx

@@ -8,12 +8,18 @@ description: "Use Oracle Database AI Vector Search as a vector store in Mem0 for
 ### Requirements
 
 - Oracle Database 23.4 or later, with a user that can create tables and vector indexes
-- The `python-oracledb` driver. In thick mode, Oracle Client 23.4 or later is also required.
+- The `python-oracledb` or `node-oracledb` driver. In thick mode, Oracle Client 23.4 or later is also required.
 
-```bash
+<CodeGroup>
+```bash Python
 pip install oracledb
 ```
 
+```bash TypeScript
+npm install oracledb
+```
+</CodeGroup>
+
 ### Usage
 
 <CodeGroup>
@@ -47,11 +53,58 @@ messages = [
 ]
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
+
+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+const config = {
+  vectorStore: {
+    provider: "oracledb",
+    config: {
+      collectionName: "mem0",
+      embeddingModelDims: 1536,
+      connectionParams: {
+        user: "mem0_user",
+        password: "your-password",
+        connectString: "localhost:1521/FREEPDB1",
+      },
+    },
+  },
+};
+
+const memory = new Memory(config);
+
+const messages = [
+  {
+    role: "user",
+    content: "I'm planning to watch a movie tonight. Any recommendations?",
+  },
+  {
+    role: "assistant",
+    content: "How about thriller movies? They can be quite engaging.",
+  },
+  {
+    role: "user",
+    content: "I'm not a big fan of thriller movies but I love sci-fi movies.",
+  },
+  {
+    role: "assistant",
+    content:
+      "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future.",
+  },
+];
+
+await memory.add(messages, {
+  userId: "alice",
+  metadata: { category: "movies" },
+});
+```
 </CodeGroup>
 
-To reuse a connection or pool you already manage, pass it as `client` instead of `connection_params`:
+To reuse a connection or pool you already manage, pass it as `client` instead of the connection parameters:
 
-```python
+<CodeGroup>
+```python Python
 import oracledb
 
 pool = oracledb.create_pool(user="mem0_user", password="your-password", dsn="localhost:1521/FREEPDB1")
@@ -64,33 +117,52 @@ config = {
 }
 ```
 
+```typescript TypeScript
+import oracledb from "oracledb";
+
+const pool = await oracledb.createPool({
+  user: "mem0_user",
+  password: "your-password",
+  connectString: "localhost:1521/FREEPDB1",
+});
+
+const config = {
+  vectorStore: {
+    provider: "oracledb",
+    config: { client: pool },
+  },
+};
+```
+</CodeGroup>
+
 ### Config
 
 Here are the parameters available for configuring Oracle AI Vector Search:
 
-| Parameter | Description | Default Value |
-| --- | --- | --- |
-| `connection_params` | Connection settings passed to `python-oracledb`, such as `user`, `password` and `dsn`. See the [connection handling guide](https://python-oracledb.readthedocs.io/en/latest/user_guide/connection_handling.html). | `None` |
-| `use_connection_pool` | Create a connection pool from `connection_params` instead of a single connection | `True` |
-| `client` | An existing `oracledb.Connection` or `oracledb.ConnectionPool` to use instead of building one from `connection_params` | `None` |
-| `collection_name` | Name of the Oracle table that stores vectors and payloads | `mem0` |
-| `embedding_model_dims` | Dimension of your embedding vectors, must be greater than 0 | `1536` |
-| `distance_metric` | Distance function used for indexing and search: `COSINE`, `EUCLIDEAN`, `EUCLIDEAN_SQUARED`, `DOT`, `HAMMING` or `MANHATTAN` | `COSINE` |
-| `do_create_index` | Whether to create a vector index on the collection | `True` |
-| `index_type` | Vector index type: `HNSW` or `IVF` | `HNSW` |
-| `index_name` | Name of the vector index | `<collection_name>_VEC_IDX` |
-| `index_parameters` | Index tuning parameters. For `HNSW`: `neighbors`, `efconstruction`. For `IVF`: `neighbor partitions`, `samples_per_partition`, `min_vectors_per_partition`. | `None` |
-| `index_accuracy` | Target index accuracy from 1 to 100, applied as `WITH TARGET ACCURACY <n>` | `None` |
+| Python | TypeScript | Description | Default Value |
+| --- | --- | --- | --- |
+| `connection_params` | `connectionParams` | Connection settings passed to the Oracle driver, such as `user`, `password` and `dsn` (`connectString` in TypeScript). See the [Python](https://python-oracledb.readthedocs.io/en/latest/user_guide/connection_handling.html) or [Node.js](https://node-oracledb.readthedocs.io/en/latest/user_guide/connection_handling.html) connection handling guide. | `None` |
+| `use_connection_pool` | `useConnectionPool` | Create a connection pool from the connection parameters instead of a single connection | `True` |
+| `client` | `client` | An existing Oracle connection or pool to use instead of building one from the connection parameters | `None` |
+| `collection_name` | `collectionName` | Name of the Oracle table that stores vectors and payloads | `mem0` |
+| `embedding_model_dims` | `embeddingModelDims` | Dimension of your embedding vectors, must be greater than 0 | `1536` |
+| `distance_metric` | `distanceMetric` | Distance function used for indexing and search: `COSINE`, `EUCLIDEAN`, `EUCLIDEAN_SQUARED`, `DOT`, `HAMMING` or `MANHATTAN` | `COSINE` |
+| `do_create_index` | `doCreateIndex` | Whether to create a vector index on the collection | `True` |
+| `index_type` | `indexType` | Vector index type: `HNSW` or `IVF` | `HNSW` |
+| `index_name` | `indexName` | Name of the vector index | `<collection_name>_VEC_IDX` |
+| `index_parameters` | `indexParameters` | Index tuning parameters. For `HNSW`: `neighbors`, `efconstruction`. For `IVF`: `neighbor partitions`, `samples_per_partition`, `min_vectors_per_partition`. | `None` |
+| `index_accuracy` | `indexAccuracy` | Target index accuracy from 1 to 100, applied as `WITH TARGET ACCURACY <n>` | `None` |
 
 <Note>
-  When you pass a pre-built `client`, Mem0 uses it as-is and ignores `connection_params` and `use_connection_pool`. Mem0 does not close a client it did not create.
+  When you pass a pre-built `client`, Mem0 uses it as-is and ignores the connection parameters and pooling options. Mem0 does not close a client it did not create.
 </Note>
 
 ### Vector indexes
 
 Set the index type with `index_type` and tune it with `index_parameters`:
 
-```python
+<CodeGroup>
+```python Python
 config = {
     "vector_store": {
         "provider": "oracledb",
@@ -104,6 +176,25 @@ config = {
 }
 ```
 
+```typescript TypeScript
+const config = {
+  vectorStore: {
+    provider: "oracledb",
+    config: {
+      connectionParams: {
+        user: "mem0_user",
+        password: "your-password",
+        connectString: "localhost:1521/FREEPDB1",
+      },
+      indexType: "HNSW",
+      indexParameters: { neighbors: 32, efconstruction: 200 },
+      indexAccuracy: 95,
+    },
+  },
+};
+```
+</CodeGroup>
+
 For the full list of supported options, see the Oracle [`CREATE VECTOR INDEX`](https://docs.oracle.com/en/database/oracle/oracle-database/26/sqlrf/create-vector-index.html) reference.
 
 ### Search scores
@@ -121,14 +212,23 @@ Filters run against the JSON `payload` column and support:
 | Comparison | `{"score": {"gte": 0.5}}`, also `eq`, `ne`, `gt`, `lt`, `lte` |
 | Membership | `{"category": {"in": ["movies", "books"]}}`, also `nin` |
 | String matching | `{"title": {"contains": "sci-fi"}}`, also `icontains` for case-insensitive |
-| Logical groups | `{"AND": [...]}`, `{"OR": [...]}`, `{"NOT": [...]}` |
+| Logical groups | `{"AND": [...]}`, `{"OR": [...]}`, `{"NOT": [...]}`, also `$and`, `$or`, `$not` |
 
 Multiple fields at the top level are combined with `AND`:
 
-```python
+<CodeGroup>
+```python Python
 m.search(
     "movie recommendations",
     user_id="alice",
     filters={"category": {"in": ["movies", "books"]}, "rating": {"gte": 4}},
 )
 ```
+
+```typescript TypeScript
+await memory.search("movie recommendations", {
+  userId: "alice",
+  filters: { category: { in: ["movies", "books"] }, rating: { gte: 4 } },
+});
+```
+</CodeGroup>

docs/core-concepts/how-it-works.mdx

@@ -46,7 +46,7 @@ When new messages arrive, Mem0 extracts durable facts and stores them with the i
 1. **Context lookup.** Mem0 checks related existing memories so it can avoid storing the same fact again.
 2. **Fact extraction.** An LLM extracts preferences, decisions, plans, and other details your agent can reuse.
 3. **Deduplication and embedding.** Redundant facts are removed, then each memory is embedded for semantic search.
-4. **Entity linking.** When configured, Mem0 links people, places, organizations, and concepts across memories.
+4. **Entity extraction.** Mem0 pulls out the people, places, organizations, and concepts each memory mentions and stores them for entity matching at search time. On Platform these entities also become the nodes of [Graph Memory](/platform/features/graph-memory).
 
 The automatic extraction path is additive. If a user says, "I moved from Austin to Seattle," Mem0 can store the new fact without silently rewriting the old one. Use explicit `update` or `delete` operations when your application needs to correct or remove a memory.
 
@@ -61,7 +61,7 @@ When you call `search`, Mem0 ranks stored memories against your query and filter
 | **Entity** | Boosts memories linked to entities in the query | Questions about a person, project, or account |
 | **Temporal** | Scores candidates on time metadata extracted at write time against the query's temporal intent | Temporal questions ("when did...", current state, recency) |
 
-Platform retrieval fuses these signals in the managed service. OSS retrieval depends on your configured vector store, optional reranker, and graph store.
+Platform retrieval fuses these signals in the managed service, where the entity signal is powered by built-in [Graph Memory](/platform/features/graph-memory). OSS retrieval depends on your configured vector store and optional reranker, and boosts on entity overlap alone: it has no graph memory.
 
 <Note>
   Always scope searches with filters such as `user_id`, `agent_id`, or `run_id`. This keeps memories from different users, agents, or sessions from mixing.
@@ -75,7 +75,7 @@ Mem0 stores different parts of a memory in stores built for different lookup pat
 |---|---|---|
 | **SQL database** | Facts and metadata | The source of truth for each memory |
 | **Vector database** | Embeddings | Semantic similarity search |
-| **Entity or graph store** | Entities and relationships | Relationship-aware retrieval when graph memory is enabled |
+| **Entity store** | Entities extracted from memory text | Boosts memories sharing entities with the query. On Platform it also backs [Graph Memory](/platform/features/graph-memory) |
 
 On Mem0 Platform, these stores are managed for you. In OSS, you choose and operate the backing stores through your configuration.
 

docs/llms.txt

@@ -177,14 +177,14 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 - [Platform CLI](https://docs.mem0.ai/platform/cli) [Platform]: Use when the user wants to manage Platform memories from the terminal.
 - [Mem0 MCP Server](https://docs.mem0.ai/platform/mem0-mcp) [Platform]: Use when connecting memory to AI coding tools over MCP.
 - [Open Source Overview](https://docs.mem0.ai/open-source/overview) [OSS]: Use when the user needs full infra control and custom provider wiring.
-- [Open Source Configuration](https://docs.mem0.ai/open-source/configuration) [OSS]: Use when configuring `Memory` - LLM, embedder, vector store, graph store.
+- [Open Source Configuration](https://docs.mem0.ai/open-source/configuration) [OSS]: Use when configuring `Memory` - LLM, embedder, vector store, reranker.
 - [Open Source Python Quickstart](https://docs.mem0.ai/open-source/python-quickstart) [OSS]: Use for the first self-hosted Python integration.
 - [Open Source Node.js Quickstart](https://docs.mem0.ai/open-source/node-quickstart) [OSS]: Use for the first self-hosted Node integration.
 - [Self-Hosted Setup](https://docs.mem0.ai/open-source/setup) [OSS]: Use when standing up the bundled REST server and dashboard via Docker Compose, including auth, API keys, and the setup wizard.
 
 ## Core Concepts
 
-- [How Mem0 Works](https://docs.mem0.ai/core-concepts/how-it-works) [Both]: Use when explaining the end-to-end pipeline: extraction (ADD-only distillation), storage across vector/graph/history stores, and multi-signal retrieval.
+- [How Mem0 Works](https://docs.mem0.ai/core-concepts/how-it-works) [Both]: Use when explaining the end-to-end pipeline: extraction (ADD-only distillation), storage across vector/entity/history stores, and multi-signal retrieval.
 - [Memory Types](https://docs.mem0.ai/core-concepts/memory-types) [Both]: Use when explaining working, factual, episodic, and semantic memory distinctions.
 - [Memory Operations - Add](https://docs.mem0.ai/core-concepts/memory-operations/add) [Both]: Use when explaining how `add()` extracts facts, resolves conflicts, and writes to both stores.
 - [Memory Operations - Search](https://docs.mem0.ai/core-concepts/memory-operations/search) [Both]: Use when explaining how queries are processed and ranked.

docs/migration/oss-v2-to-v3.mdx

@@ -1,6 +1,6 @@
 ---
 title: "Open Source: Migrating to the New Memory Algorithm"
-description: "Guide for self-hosted Mem0 users to upgrade to the new memory algorithm with ADD-only extraction, hybrid search, and entity linking."
+description: "Guide for self-hosted Mem0 users to upgrade to the new memory algorithm with ADD-only extraction, hybrid search, and entity-aware retrieval."
 icon: "arrow-right"
 iconType: "solid"
 ---
@@ -15,7 +15,8 @@ The new Mem0 release redesigns both extraction and retrieval, and cleans up the
 
 - **Extraction**: Single-pass ADD-only (one LLM call, no UPDATE/DELETE)
 - **Retrieval**: Multi-signal hybrid search (semantic + BM25 keyword + entity matching)
-- **Entity linking**: Automatic entity extraction and cross-memory linking
+- **Entity matching**: Automatic entity extraction feeds a third scoring signal in hybrid search, boosting memories that share entities with the query
+- **Graph memory moved to Platform**: The external graph store integration is removed from OSS; graph memory is now a built-in, always-on [Mem0 Platform feature](/platform/features/graph-memory)
 - **SDK cleanup**: Deprecated parameters removed, naming conventions standardized
 - **API surface aligned with Platform**: Entity IDs now follow the same convention across OSS and Platform: top-level kwargs for `add()` / `delete_all()`, inside `filters` for `search()` / `get_all()`
 
@@ -37,7 +38,7 @@ These changes produce a **+20 point improvement on LoCoMo** (71.4 → 91.6) and
 | `add()` events | Returns `ADD`, `UPDATE`, `DELETE` | Returns `ADD` only | Update code expecting UPDATE/DELETE |
 | Custom extraction prompt | `custom_fact_extraction_prompt` | `custom_instructions` | Rename in config |
 | Custom update prompt | `custom_update_memory_prompt` | Deprecated | Use `custom_instructions` instead |
-| Graph memory | `enable_graph` + `graph_store` in config | Removed | Graph store support has been removed entirely |
+| Graph memory | `enable_graph` + `graph_store` in config | Removed | Graph memory is removed from OSS. It's a built-in, always-on [Mem0 Platform feature](/platform/features/graph-memory) |
 | Qdrant client | `>=1.9.1` | `>=1.12.0` | Update dependency |
 | Upstash client | `>=0.1.0` | `>=0.6.0` | Update dependency |
 
@@ -53,8 +54,8 @@ These changes produce a **+20 point improvement on LoCoMo** (71.4 → 91.6) and
 | `messages` in `add()` | Could be `null` / `undefined` | Required: throws on null/undefined | Always pass a string or array |
 | Payload key for lemmatized text | `text_lemmatized` (snake_case) | `textLemmatized` (camelCase) | TS-only internal field. If you share a vector store collection between Python and TS SDKs, lemma-based BM25 will not resolve across languages: keep collections language-scoped. |
 | Custom prompt | `customPrompt` | `customInstructions` | Rename in config |
-| Graph memory | `enableGraph` + `graphStore` in config | Removed | Graph store support has been removed entirely |
-| Default graph config | Neo4j default config applied | No default graph config | Graph store config is no longer used |
+| Graph memory | `enableGraph` + `graphStore` in config | Removed | Graph memory is removed from OSS. It's a built-in, always-on [Mem0 Platform feature](/platform/features/graph-memory) |
+| Default graph config | Neo4j default config applied | No default graph config | Graph store config is no longer read; OSS has no built-in graph config to fall back to |
 
 ### Python Client SDK
 
@@ -104,7 +105,7 @@ These changes produce a **+20 point improvement on LoCoMo** (71.4 → 91.6) and
 </Tabs>
 
 <Info>
-The Python `[nlp]` extra installs [spaCy](https://spacy.io/) for entity extraction and keyword lemmatization. Without it, Mem0 still works but falls back to semantic-only search (no entity linking, no BM25 lemmatization).
+The Python `[nlp]` extra installs [spaCy](https://spacy.io/) for entity extraction and keyword lemmatization. Without it, Mem0 still works but falls back to semantic-only search (no entity matching, no BM25 lemmatization).
 </Info>
 
 <Warning>
@@ -135,7 +136,7 @@ pip install fastembed
     config = {
         "custom_instructions": "Focus on user preferences",  # [OK] New name
         # custom_update_memory_prompt removed: use custom_instructions
-        # enable_graph and graph_store removed: graph store support has been removed
+        # enable_graph and graph_store removed: graph memory is now a Mem0 Platform feature
     }
     ```
   </Tab>
@@ -154,7 +155,7 @@ pip install fastembed
     // After
     const config = {
       customInstructions: "Focus on user preferences",  // [OK] New name
-      // enableGraph and graphStore removed: graph store support has been removed
+      // enableGraph and graphStore removed: graph memory is now a Mem0 Platform feature
     };
     ```
   </Tab>
@@ -320,35 +321,31 @@ pip install "qdrant-client>=1.12.0"
 pip install "upstash-vector>=0.6.0"
 ```
 
-### 6. Entity Store Setup
+### 6. Entity Matching Store Setup
 
-The new algorithm automatically creates a parallel entity store collection named `{your_collection}_entities`. No manual setup is required: it's created on first use.
+The new algorithm automatically creates a parallel collection named `{your_collection}_entities` to power entity matching, the third signal in hybrid search. No manual setup is required: it's created on first use. This is separate from and unrelated to graph memory, which is a Mem0 Platform feature.
 
 <Warning>
 Make sure your vector store user/credentials have permission to create new collections. If you're using a managed vector database with restricted permissions, pre-create the `{collection_name}_entities` collection with the same embedding dimensions as your main collection.
 </Warning>
 
-## Graph Memory: Now Built-In
+## Graph Memory: Platform Only
 
-External graph **store** support has been removed from the open-source SDK and replaced by **built-in graph memory** (entity linking), which runs natively with no external dependencies.
+Graph memory is removed from the open-source SDK. It is not being replaced by an OSS equivalent: graph memory is a **Mem0 Platform** feature, built in and always on, with no external graph database required. See [Graph Memory](/platform/features/graph-memory) for what it does on Platform.
 
-**What was removed:**
+**What was removed from OSS:**
 - `enable_graph` / `enableGraph` config flag
-- `graph_store` / `graphStore` configuration block (Neo4j, Memgraph, Kuzu, Apache AGE, Neptune)
-- All external graph store code paths (~4000 lines)
-
-**What replaces it:**
-
-Mem0 now builds the graph itself. It extracts entities (proper nouns, quoted text, compound noun phrases) from every memory during the add pipeline and stores them in a parallel collection (`{collection}_entities`) inside your existing vector store. Memories that share an entity are linked, and at search time entities from the query are matched against this collection to boost connected memories. The boost is folded into the combined `score` on each result.
+- `graph_store` / `graphStore` configuration block
+- All external graph store drivers (Neo4j, Memgraph, Kuzu, Apache AGE, Neptune) and their code paths (~4000 lines)
 
 **Migration:**
 - Remove `enable_graph` / `enableGraph` from your config
 - Remove the `graph_store` / `graphStore` block: it is no longer read
 - Uninstall external graph drivers (neo4j, memgraph, etc.) if you were using them only for Mem0
-- No data migration is required. Built-in graph memory activates automatically on the next `add()` call.
+- If you need graph memory, use [Mem0 Platform](/platform/features/graph-memory) instead of self-hosted OSS
 
 <Warning>
-The old `relations` field on search results (populated by the external graph store) is no longer returned. Entity connections are now applied through retrieval ranking rather than exposed as a separate, directly traversable structure. If your application read or traversed the `relations` array, you will need to redesign that part against the new API.
+The old `relations` field on search results (populated by the external graph store) is no longer returned in OSS. OSS has no graph memory replacement, so there is nothing to populate this field with. If your application read or traversed the `relations` array, either move to Mem0 Platform to keep that data or redesign that part against the new OSS retrieval API.
 </Warning>
 
 ## How the New Algorithm Works
@@ -362,7 +359,7 @@ Input conversation
     → Batch embed extracted memories
     → Hash-based deduplication (MD5, prevents exact duplicates)
     → Batch insert into vector store
-    → Entity extraction + linking
+    → Entity extraction (for entity matching)
 ```
 
 The previous algorithm used two LLM calls: one to extract candidate facts, one to decide ADD/UPDATE/DELETE actions against existing memories. The new algorithm collapses this into a single call that only adds. The model spends its capacity on understanding the input rather than diffing against existing state.
@@ -375,7 +372,7 @@ Query
     → Parallel scoring:
         1. Semantic search (vector similarity)
         2. BM25 keyword search (normalized term matching)
-        3. Entity matching (entity graph boost)
+        3. Entity matching (entity overlap boost)
     → Score fusion → Top-K selection
 ```
 
@@ -408,8 +405,8 @@ The new features degrade gracefully when optional dependencies are missing:
 | Missing Dependency | Impact | Search Still Works? |
 |---|---|---|
 | spaCy (`mem0ai[nlp]`) | No entity extraction, no BM25 lemmatization | Yes (semantic-only) |
-| `fastembed` (Qdrant) | No BM25 keyword search | Yes (semantic + entity) |
-| Entity store unavailable | No entity boosting | Yes (semantic + BM25) |
+| `fastembed` (Qdrant) | No BM25 keyword search | Yes (semantic + entity matching) |
+| Entity matching store unavailable | No entity matching boost | Yes (semantic + BM25) |
 
 You always get semantic search. Hybrid search features layer on top when available.
 
@@ -449,13 +446,13 @@ These parameters have been removed across all SDKs. Remove them from your code:
 
 **Config:** `custom_update_memory_prompt` → deprecated, use `custom_instructions`
 
-**Config:** `enable_graph` + `graph_store` → removed (graph store support removed entirely)
+**Config:** `enable_graph` + `graph_store` → removed (graph memory is now a [Mem0 Platform feature](/platform/features/graph-memory))
 
 ### TypeScript OSS: Removed/renamed parameters
 
 **Config:** `customPrompt` → renamed to `customInstructions`
 
-**Config:** `enableGraph` + `graphStore` → removed (graph store support removed entirely)
+**Config:** `enableGraph` + `graphStore` → removed (graph memory is now a [Mem0 Platform feature](/platform/features/graph-memory))
 
 **search():** `limit` → renamed to `topK`
 
@@ -521,9 +518,9 @@ If spaCy is not installed at all, install the NLP extras:
 pip install "mem0ai[nlp]"
 ```
 
-### Entity store collection creation fails
+### Entity matching store collection creation fails
 
-The entity store tries to create a `{collection_name}_entities` collection automatically. If your vector database has restricted permissions, pre-create this collection with the same embedding dimensions as your main collection.
+The entity matching store tries to create a `{collection_name}_entities` collection automatically. If your vector database has restricted permissions, pre-create this collection with the same embedding dimensions as your main collection.
 
 ### Score values are different from before
 

docs/open-source/configuration.mdx

@@ -4,7 +4,7 @@ description: "Configure Mem0 OSS in Python or TypeScript with your own LLM, embe
 icon: "sliders"
 ---
 
-Mem0 OSS works out of the box with OpenAI defaults. Point it at your own LLM, embedder, and vector store by passing a config when you create `Memory`. The Python SDK also supports a reranker and graph memory.
+Mem0 OSS works out of the box with OpenAI defaults. Point it at your own LLM, embedder, vector store, and reranker by passing a config when you create `Memory`.
 
 <Info>
   **Prerequisites**
@@ -90,11 +90,11 @@ Set your provider keys as environment variables:
 
 ```bash
 export OPENAI_API_KEY="..."
-export COHERE_API_KEY="..."   # Python reranker only
+export COHERE_API_KEY="..."   # Cohere reranker only
 ```
 
 <Note>
-  The TypeScript OSS SDK configures the LLM, embedder, vector store, and history store. Reranker and graph memory are Python-only today.
+  The TypeScript OSS SDK configures the LLM, embedder, vector store, history store, and reranker. Graph memory is not part of OSS in either language: it is a built-in [Mem0 Platform feature](/platform/features/graph-memory).
 </Note>
 
 Prefer a config file? Load YAML into Python's `from_config`:

docs/openapi.json

@@ -2784,6 +2784,10 @@
 										"type": "string",
 										"description": "Project-level instructions that guide extraction for this call."
 									},
+									"agent_custom_instructions": {
+										"type": "string",
+										"description": "Extraction instructions for agent-scoped memories, overriding the project-level setting for this call. Applied when `agent_id` is sent without `user_id`; when both are sent it governs the assistant-attributed memories while `custom_instructions` governs the rest."
+									},
 									"custom_categories": {
 										"type": "array",
 										"description": "Category catalog for this call. Replaces the project-level list rather than merging with it. Omit to fall back to the project list, then the default catalog.",
@@ -5805,6 +5809,11 @@
 										},
 										"description": "Custom instructions for memory processing in this project"
 									},
+									"agent_custom_instructions": {
+										"type": "string",
+										"nullable": true,
+										"description": "Extraction instructions for agent-scoped memories. Falls back to `custom_instructions` when unset. Send an empty string to clear it."
+									},
 									"custom_categories": {
 										"type": "array",
 										"items": {
@@ -7431,6 +7440,12 @@
 						"type": "string",
 						"nullable": true
 					},
+					"agent_custom_instructions": {
+						"description": "Extraction instructions that apply only to agent-scoped memories. Used when `agent_id` is sent without `user_id`; when both are sent it governs the assistant-attributed memories while `custom_instructions` governs the rest. Falls back to `custom_instructions` when unset.",
+						"title": "Agent custom instructions",
+						"type": "string",
+						"nullable": true
+					},
 					"immutable": {
 						"description": "Whether the memory is immutable.",
 						"title": "Immutable",

docs/platform/features/custom-instructions.mdx

@@ -95,6 +95,100 @@ Exclude:
 - [Irrelevant information]
 ```
 
+## Agent Custom Instructions
+
+`custom_instructions` applies to every memory your project extracts, no matter whose it is. But what is worth remembering about an agent is rarely what is worth remembering about a user: an agent's useful memories are things like which tools fail, which retry strategies work, and how a given environment behaves, not personal preferences.
+
+`agent_custom_instructions` is an optional second set of extraction rules that applies only to agent-scoped memories.
+
+Available from Python SDK `v2.0.17` and TypeScript SDK `v3.1.5`. Upgrade first if you are on an earlier release.
+
+Set it on the project alongside `custom_instructions`:
+
+<CodeGroup>
+```python Python
+client.project.update(
+    custom_instructions="Extract the user's preferences, goals, and constraints.",
+    agent_custom_instructions=(
+        "Extract operational lessons for the agent:\n"
+        "- Tools that failed and the error returned\n"
+        "- Retry or fallback strategies that worked\n"
+        "- Environment quirks worth recalling on the next run\n\n"
+        "Exclude: user preferences, personal details."
+    ),
+)
+```
+
+```javascript JavaScript
+await client.updateProject({
+  customInstructions: "Extract the user's preferences, goals, and constraints.",
+  agentCustomInstructions: `Extract operational lessons for the agent:
+- Tools that failed and the error returned
+- Retry or fallback strategies that worked
+- Environment quirks worth recalling on the next run
+
+Exclude: user preferences, personal details.`,
+});
+```
+</CodeGroup>
+
+### Which instructions apply
+
+Which set governs an `add()` call depends on the entity IDs you pass with it:
+
+| The add call passes | Instructions applied |
+|---------------------|----------------------|
+| `user_id` only | `custom_instructions` |
+| `agent_id` only | `agent_custom_instructions` |
+| `user_id` **and** `agent_id` | `agent_custom_instructions` govern the memories attributed to the assistant; `custom_instructions` govern the rest |
+
+`agent_custom_instructions` is unset by default. While it is unset, `custom_instructions` applies to every memory, so projects that don't set it behave exactly as they did before.
+
+### Overriding for a single call
+
+Both fields are also accepted per request, overriding the project setting for that `add()` only:
+
+<CodeGroup>
+```python Python
+client.add(
+    messages,
+    filters={"agent_id": "support-agent"},
+    agent_custom_instructions="Only remember which tools errored and why.",
+)
+```
+
+```javascript JavaScript
+await client.add(messages, {
+  agentId: "support-agent",
+  agentCustomInstructions: "Only remember which tools errored and why.",
+});
+```
+</CodeGroup>
+
+### Reading and clearing
+
+<CodeGroup>
+```python Python
+# Read the current value
+response = client.project.get(fields=["agent_custom_instructions"])
+print(response["agent_custom_instructions"])
+
+# Clear it; agent memories fall back to custom_instructions
+client.project.update(agent_custom_instructions="")
+```
+
+```javascript JavaScript
+// Read the current value
+const response = await client.getProject({
+  fields: ["agentCustomInstructions"],
+});
+console.log(response.agentCustomInstructions);
+
+// Clear it; agent memories fall back to customInstructions
+await client.updateProject({ agentCustomInstructions: "" });
+```
+</CodeGroup>
+
 ## Real-World Examples
 
 <Tabs>

mem0-ts/package.json

@@ -1,6 +1,6 @@
 {
   "name": "mem0ai",
-  "version": "3.1.4",
+  "version": "3.1.5",
   "description": "The Memory Layer For Your AI Apps",
   "main": "./dist/index.js",
   "module": "./dist/index.mjs",
@@ -86,6 +86,7 @@
   "license": "Apache-2.0",
   "devDependencies": {
     "@types/better-sqlite3": "^7.6.13",
+    "@types/oracledb": "^7.0.1",
     "@types/node": "^22.7.6",
     "@types/uuid": "^9.0.8",
     "dotenv": "^16.4.5",
@@ -139,6 +140,7 @@
     "mongodb": "^7.0.0",
     "weaviate-client": "^3.0.0",
     "ollama": "^0.5.14",
+    "oracledb": "^6.5.0 || ^7.0.0",
     "pg": "8.11.3",
     "redis": "^4.6.13",
     "@elastic/elasticsearch": "^9.0.0",
@@ -252,6 +254,9 @@
     },
     "iovalkey": {
       "optional": true
+    },
+    "oracledb": {
+      "optional": true
     }
   },
   "engines": {

mem0-ts/pnpm-lock.yaml

@@ -153,6 +153,9 @@ importers:
       openai:
         specifier: ^4.93.0
         version: 4.104.0(ws@5.2.5)(zod@3.25.76)
+      oracledb:
+        specifier: ^6.5.0 || ^7.0.0
+        version: 7.0.1
       pg:
         specifier: 8.11.3
         version: 8.11.3
@@ -181,6 +184,9 @@ importers:
       '@types/node':
         specifier: ^22.7.6
         version: 22.19.21
+      '@types/oracledb':
+        specifier: ^7.0.1
+        version: 7.0.1
       '@types/uuid':
         specifier: ^9.0.8
         version: 9.0.8
@@ -1911,6 +1917,9 @@ packages:
   '@types/normalize-package-data@2.4.4':
     resolution: {integrity: sha512-37i+OaWTh9qeK4LSHPsyRC7NahnGotNuZvjLSgcPzblpHB3rrCJxAOgI5gCdKm7coonsaX1Of0ILiTcnZjbfxA==}
 
+  '@types/oracledb@7.0.1':
+    resolution: {integrity: sha512-0A6m9YE4yu73KXehr5D6cbyALUzZoANGY4bG5cAPQIpJoJG4eMVPbR1Vau8ycnC25V/+F4Au1pdFSy8ODOAD0w==}
+
   '@types/pad-left@2.1.1':
     resolution: {integrity: sha512-Xd22WCRBydkGSApl5Bw0PhAOHKSVjNL3E3AwzKaps96IMraPqy5BvZIsBVK6JLwdybUzjHnuWVwpDd0JjTfHXA==}
 
@@ -3796,6 +3805,10 @@ packages:
   openid-client@5.7.1:
     resolution: {integrity: sha512-jDBPgSVfTnkIh71Hg9pRvtJc6wTwqjRkN88+gCFtYWrlP4Yx2Dsrow8uPi3qLr/aeymPF3o2+dS+wOpglK04ew==}
 
+  oracledb@7.0.1:
+    resolution: {integrity: sha512-xlM0Ceh6A5stQLAdEfKf3pgCSkbOjQLo2ZPEi3+kXklz+KbZD3fLi/nsTSbQeZZNFBSFDNxdn1Ek3+bxG40M8w==}
+    engines: {node: '>=14.17'}
+
   p-finally@1.0.0:
     resolution: {integrity: sha512-LICb2p9CB7FS+0eR1oqWnHhp0FljGLZCWBE9aix0Uye9W8LTQPwMTYVGWQWIw9RdQiDg4+epXQODwIYJtSJaow==}
     engines: {node: '>=4'}
@@ -7247,6 +7260,10 @@ snapshots:
 
   '@types/normalize-package-data@2.4.4': {}
 
+  '@types/oracledb@7.0.1':
+    dependencies:
+      '@types/node': 22.19.21
+
   '@types/pad-left@2.1.1': {}
 
   '@types/pg@8.11.0':
@@ -9349,6 +9366,8 @@ snapshots:
       object-hash: 2.2.0
       oidc-token-hash: 5.2.0
 
+  oracledb@7.0.1: {}
+
   p-finally@1.0.0: {}
 
   p-limit@2.3.0:

mem0-ts/src/client/mem0.ts

@@ -81,6 +81,8 @@ class APIError extends Error {
 interface ClientOptions {
   apiKey: string;
   host?: string;
+  /** Max cached identities per process. Defaults to 50. */
+  identityCacheMax?: number;
 }
 
 interface ClientIdentity {
@@ -90,7 +92,7 @@ interface ClientIdentity {
 }
 
 // Shares one ping per (host, api key) across clients; FIFO-capped.
-const IDENTITY_CACHE_MAX = 50;
+const IDENTITY_CACHE_MAX_DEFAULT = 50;
 const identityByCredentials = new Map<string, Promise<ClientIdentity>>();
 
 export default class MemoryClient {
@@ -102,6 +104,7 @@ export default class MemoryClient {
   client: any;
   telemetryId: string;
   private initialized: Promise<void>;
+  private identityCacheMax: number;
 
   _validateApiKey(): any {
     if (!this.apiKey) {
@@ -120,6 +123,8 @@ export default class MemoryClient {
     this.host = options.host || "https://api.mem0.ai";
     this.organizationId = null;
     this.projectId = null;
+    this.identityCacheMax =
+      options.identityCacheMax ?? IDENTITY_CACHE_MAX_DEFAULT;
 
     this.headers = {
       Authorization: `Token ${this.apiKey}`,
@@ -136,7 +141,7 @@ export default class MemoryClient {
 
     this.telemetryId = "";
 
-    // Requests never wait on this; only telemetry does.
+    // Memory requests never wait on this; telemetry and _awaitIdentity do.
     this.initialized = this._resolveIdentity();
   }
 
@@ -146,7 +151,7 @@ export default class MemoryClient {
     let shared = identityByCredentials.get(credentials);
     if (!shared) {
       shared = this._initializeClient();
-      if (identityByCredentials.size >= IDENTITY_CACHE_MAX) {
+      if (identityByCredentials.size >= this.identityCacheMax) {
         identityByCredentials.delete(
           identityByCredentials.keys().next().value!,
         );
@@ -165,6 +170,11 @@ export default class MemoryClient {
     });
   }
 
+  // Blocks until the ping has populated organizationId/projectId.
+  private async _awaitIdentity(): Promise<void> {
+    await this.initialized;
+  }
+
   private async _initializeClient(): Promise<ClientIdentity> {
     try {
       await this.ping();
@@ -616,6 +626,7 @@ export default class MemoryClient {
     const payloadKeys = Object.keys(options || {});
     this._captureEvent("get_project", [payloadKeys]);
     const { fields } = options;
+    await this._awaitIdentity();
 
     if (!(this.organizationId && this.projectId)) {
       throw new Error(
@@ -639,6 +650,7 @@ export default class MemoryClient {
     prompts: PromptUpdatePayload,
   ): Promise<Record<string, any>> {
     this._captureEvent("update_project", []);
+    await this._awaitIdentity();
     if (!(this.organizationId && this.projectId)) {
       throw new Error(
         "organizationId and projectId must be set to update instructions or categories",
@@ -659,7 +671,11 @@ export default class MemoryClient {
   // WebHooks
   async getWebhooks(data?: { projectId?: string }): Promise<Array<Webhook>> {
     this._captureEvent("get_webhooks", []);
+    if (!data?.projectId) await this._awaitIdentity();
     const project_id = data?.projectId || this.projectId;
+    if (!project_id) {
+      throw new Error("projectId must be set to access webhooks");
+    }
     const response = await this._fetchWithErrorHandling(
       `${this.host}/api/v1/webhooks/projects/${project_id}/`,
       {
@@ -671,6 +687,10 @@ export default class MemoryClient {
 
   async createWebhook(webhook: WebhookCreatePayload): Promise<Webhook> {
     this._captureEvent("create_webhook", []);
+    await this._awaitIdentity();
+    if (!this.projectId) {
+      throw new Error("projectId must be set to create a webhook");
+    }
     const body = {
       name: webhook.name,
       url: webhook.url,

mem0-ts/src/client/mem0.types.ts

@@ -12,6 +12,7 @@ export interface AddMemoryOptions extends EntityOptions {
   infer?: boolean;
   customCategories?: custom_categories[];
   customInstructions?: string;
+  agentCustomInstructions?: string;
   timestamp?: number;
   expirationDate?: string;
   structuredDataSchema?: Record<string, any>;
@@ -60,6 +61,7 @@ export interface ProjectOptions {
 
 export interface PromptUpdatePayload {
   customInstructions?: string;
+  agentCustomInstructions?: string;
   customCategories?: custom_categories[];
   version?: string;
   memoryDepth?: string | null;
@@ -174,6 +176,7 @@ export interface PaginatedMemories {
 
 export interface ProjectResponse {
   customInstructions?: string;
+  agentCustomInstructions?: string;
   // The API returns category objects (`[{ "<name>": "<description>" }]`),
   // not bare strings (see issue #5738).
   customCategories?: custom_categories[];

mem0-ts/src/client/tests/memoryClient.crud.test.ts

@@ -74,6 +74,35 @@ describe("MemoryClient - add()", () => {
     expect(getFetchBody(call!).expiration_date).toBe("2030-01-31");
   });
 
+  test("serializes agentCustomInstructions as agent_custom_instructions", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/v3/memories/add/", { status: 200, body: [createMockMemory()] });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.add([{ role: "user", content: "test" }], {
+      agentId: "a1",
+      agentCustomInstructions: "Remember tool failures",
+    });
+
+    const call = findFetchCall(mock, "/v3/memories/add/", "POST");
+    expect(getFetchBody(call!).agent_custom_instructions).toBe(
+      "Remember tool failures",
+    );
+  });
+
+  test("omits agent_custom_instructions when it is not passed", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/v3/memories/add/", { status: 200, body: [createMockMemory()] });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.add([{ role: "user", content: "test" }], { userId: "u1" });
+
+    const call = findFetchCall(mock, "/v3/memories/add/", "POST");
+    expect(getFetchBody(call!)).not.toHaveProperty("agent_custom_instructions");
+  });
+
   test("throws an error when given an empty messages array", async () => {
     setupMockFetch();
 

mem0-ts/src/client/tests/memoryClient.identity.test.ts

@@ -0,0 +1,228 @@
+/**
+ * MemoryClient unit tests — org/project identity resolution ordering.
+ *
+ * Each test calls the method under test as the first awaited operation on a
+ * fresh client. Any earlier await on the instance resolves identity and voids
+ * the test.
+ */
+import { MemoryClient } from "../mem0";
+import { TEST_ORG_ID, TEST_PROJECT_ID } from "./helpers";
+import { setupMockFetch, installConsoleSuppression } from "./setup";
+
+installConsoleSuppression();
+
+// Distinct key per client keeps each test off the module-scope identity cache.
+let keySeq = 0;
+const freshClient = () =>
+  new MemoryClient({ apiKey: `test-api-key-identity-${keySeq++}` });
+
+// Selects by path; the ping and PostHog calls also land in the mock.
+const findUrlOrNone = (mock: jest.Mock, needle: string): string | undefined =>
+  mock.mock.calls
+    .map((c: [string, RequestInit]) => c[0])
+    .find((u: string) => u.includes(needle));
+
+const findUrl = (mock: jest.Mock, needle: string): string => {
+  const url = findUrlOrNone(mock, needle);
+  expect(url).toBeDefined();
+  return url as string;
+};
+
+describe("MemoryClient - project-scoped URLs on a fresh client", () => {
+  test("getProject uses the resolved org and project ids", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { custom_instructions: "Be helpful" },
+    });
+    const mock = setupMockFetch(extra);
+
+    await freshClient().getProject({ fields: ["custom_instructions"] });
+
+    const url = findUrl(mock, "/api/v1/orgs/organizations/");
+    expect(url).toContain(`/api/v1/orgs/organizations/${TEST_ORG_ID}/`);
+    expect(url).toContain(`/projects/${TEST_PROJECT_ID}/`);
+  });
+
+  test("updateProject uses the resolved org and project ids", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { custom_instructions: "Updated" },
+    });
+    const mock = setupMockFetch(extra);
+
+    await freshClient().updateProject({ customInstructions: "Updated" });
+
+    const url = findUrl(mock, "/api/v1/orgs/organizations/");
+    expect(url).toContain(`/api/v1/orgs/organizations/${TEST_ORG_ID}/`);
+    expect(url).toContain(`/projects/${TEST_PROJECT_ID}/`);
+  });
+
+  test("getWebhooks targets the resolved project, not null", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/webhooks/projects/", { status: 200, body: [] });
+    const mock = setupMockFetch(extra);
+
+    await freshClient().getWebhooks();
+
+    const url = findUrl(mock, "/api/v1/webhooks/projects/");
+    expect(url).toContain(`/api/v1/webhooks/projects/${TEST_PROJECT_ID}/`);
+    expect(url).not.toContain("/projects/null/");
+    expect(url).not.toContain("/projects/undefined/");
+  });
+
+  test("createWebhook targets the resolved project, not null", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/webhooks/projects/", {
+      status: 200,
+      body: { webhook_id: "wh_1" },
+    });
+    const mock = setupMockFetch(extra);
+
+    await freshClient().createWebhook({
+      name: "hook",
+      url: "https://example.com/hook",
+      eventTypes: ["memory_add"],
+    });
+
+    const url = findUrl(mock, "/api/v1/webhooks/projects/");
+    expect(url).toContain(`/api/v1/webhooks/projects/${TEST_PROJECT_ID}/`);
+    expect(url).not.toContain("/projects/null/");
+    expect(url).not.toContain("/projects/undefined/");
+  });
+
+  test("an explicit projectId is honored without waiting on identity", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/webhooks/projects/", { status: 200, body: [] });
+    const mock = setupMockFetch(extra);
+
+    await freshClient().getWebhooks({ projectId: "proj_explicit_789" });
+
+    expect(findUrl(mock, "/api/v1/webhooks/projects/")).toContain(
+      "/api/v1/webhooks/projects/proj_explicit_789/",
+    );
+  });
+});
+
+describe("MemoryClient - memory endpoints do not wait on identity", () => {
+  test("search completes while the ping is still pending", async () => {
+    // The ping never settles.
+    const mock = jest.fn((url: string) => {
+      if (url.includes("/v1/ping/")) return new Promise(() => {});
+      return Promise.resolve({
+        ok: true,
+        status: 200,
+        json: () => Promise.resolve({ results: [] }),
+        text: () => Promise.resolve(""),
+      });
+    });
+    global.fetch = mock as unknown as typeof global.fetch;
+
+    await expect(
+      freshClient().search("query", { filters: { user_id: "alice" } }),
+    ).resolves.toBeDefined();
+
+    expect(findUrl(mock, "/v3/memories/search/")).toBeDefined();
+  });
+});
+
+describe("MemoryClient - identity cache overflow", () => {
+  const pingCount = (mock: jest.Mock) =>
+    mock.mock.calls.filter((c: [string, RequestInit]) =>
+      c[0].includes("/v1/ping/"),
+    ).length;
+
+  // The cache is module scope, so each test needs its own module registry.
+  const isolatedClient = (): typeof MemoryClient => {
+    jest.resetModules();
+    // eslint-disable-next-line @typescript-eslint/no-require-imports
+    return require("../mem0").MemoryClient;
+  };
+
+  const projectOk = () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", { status: 200, body: {} });
+    return setupMockFetch(extra);
+  };
+
+  test("a reused credential pair pings once", async () => {
+    const mock = projectOk();
+    const Client = isolatedClient();
+
+    const opts = { apiKey: "cache-warm-key", identityCacheMax: 1 };
+    await new Client(opts).getProject({ fields: [] });
+    await new Client(opts).getProject({ fields: [] });
+
+    expect(pingCount(mock)).toBe(1);
+  });
+
+  test("an evicted credential pair re-pings and still resolves identity", async () => {
+    const mock = projectOk();
+    const Client = isolatedClient();
+    const opts = (apiKey: string) => ({ apiKey, identityCacheMax: 1 });
+
+    await new Client(opts("key-a")).getProject({ fields: [] });
+    // Evicts key-a.
+    await new Client(opts("key-b")).getProject({ fields: [] });
+    expect(pingCount(mock)).toBe(2);
+
+    await new Client(opts("key-a")).getProject({ fields: [] });
+
+    // Eviction costs a ping; it never yields an unresolved identity.
+    expect(pingCount(mock)).toBe(3);
+    expect(findUrl(mock, "/api/v1/orgs/organizations/")).toContain(
+      `/api/v1/orgs/organizations/${TEST_ORG_ID}/`,
+    );
+  });
+});
+
+describe("MemoryClient - unresolved identity", () => {
+  const pingFails = () => {
+    const mock = jest.fn((url: string) => {
+      if (url.includes("/v1/ping/")) {
+        return Promise.resolve({
+          ok: false,
+          status: 500,
+          text: () => Promise.resolve("boom"),
+          json: () => Promise.resolve({}),
+        });
+      }
+      return Promise.resolve({
+        ok: true,
+        status: 200,
+        json: () => Promise.resolve([]),
+        text: () => Promise.resolve(""),
+      });
+    });
+    global.fetch = mock as unknown as typeof global.fetch;
+    return mock;
+  };
+
+  test("getProject reports the unset ids", async () => {
+    pingFails();
+    await expect(freshClient().getProject({ fields: [] })).rejects.toThrow(
+      "organizationId and projectId must be set",
+    );
+  });
+
+  test("getWebhooks reports the unset project instead of requesting null", async () => {
+    const mock = pingFails();
+    await expect(freshClient().getWebhooks()).rejects.toThrow(
+      "projectId must be set",
+    );
+    expect(findUrlOrNone(mock, "/api/v1/webhooks/")).toBeUndefined();
+  });
+
+  test("createWebhook reports the unset project instead of requesting null", async () => {
+    const mock = pingFails();
+    await expect(
+      freshClient().createWebhook({
+        name: "hook",
+        url: "https://example.com/hook",
+        eventTypes: ["memory_add"],
+      }),
+    ).rejects.toThrow("projectId must be set");
+    expect(findUrlOrNone(mock, "/api/v1/webhooks/")).toBeUndefined();
+  });
+});

mem0-ts/src/client/tests/memoryClient.project.test.ts

@@ -96,6 +96,84 @@ describe("MemoryClient - updateProject()", () => {
       "Updated instructions",
     );
   });
+
+  test("camelCases agentCustomInstructions into agent_custom_instructions", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { message: "Updated" },
+    });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.ping();
+    await client.updateProject({
+      agentCustomInstructions: "Remember tool failures",
+    });
+
+    const call = findFetchCall(mock, "/api/v1/orgs/organizations/", "PATCH");
+    expect(getFetchBody(call!).agent_custom_instructions).toBe(
+      "Remember tool failures",
+    );
+  });
+
+  test("sends both instruction sets in one PATCH", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { message: "Updated" },
+    });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.ping();
+    await client.updateProject({
+      customInstructions: "Remember user preferences",
+      agentCustomInstructions: "Remember tool failures",
+    });
+
+    const body = getFetchBody(
+      findFetchCall(mock, "/api/v1/orgs/organizations/", "PATCH")!,
+    );
+    expect(body.custom_instructions).toBe("Remember user preferences");
+    expect(body.agent_custom_instructions).toBe("Remember tool failures");
+  });
+
+  test("an empty string round-trips, so the field can be cleared", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { message: "Updated" },
+    });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.ping();
+    await client.updateProject({ agentCustomInstructions: "" });
+
+    const body = getFetchBody(
+      findFetchCall(mock, "/api/v1/orgs/organizations/", "PATCH")!,
+    );
+    expect(body).toHaveProperty("agent_custom_instructions", "");
+  });
+
+  test("omits agent_custom_instructions when it is not passed", async () => {
+    const extra = new Map<string, { status: number; body: unknown }>();
+    extra.set("/api/v1/orgs/organizations/", {
+      status: 200,
+      body: { message: "Updated" },
+    });
+    const mock = setupMockFetch(extra);
+
+    const client = new MemoryClient({ apiKey: TEST_API_KEY });
+    await client.ping();
+    await client.updateProject({ customInstructions: "Be helpful" });
+
+    const body = getFetchBody(
+      findFetchCall(mock, "/api/v1/orgs/organizations/", "PATCH")!,
+    );
+    expect(body).not.toHaveProperty("agent_custom_instructions");
+  });
 });
 
 // ─── feedback() ─────────────────────────────────────────

mem0-ts/src/oss/src/index.ts

@@ -51,6 +51,7 @@ export * from "./vector_stores/milvus";
 export * from "./vector_stores/mongodb";
 export * from "./vector_stores/opensearch";
 export * from "./vector_stores/weaviate";
+export * from "./vector_stores/oracledb";
 export * from "./rerankers/base";
 export * from "./rerankers/cohere";
 export * from "./rerankers/llm";

mem0-ts/src/oss/src/utils/factory.ts

@@ -71,6 +71,7 @@ import { TurbopufferDB } from "../vector_stores/turbopuffer";
 import { Milvus } from "../vector_stores/milvus";
 import { MongoDB } from "../vector_stores/mongodb";
 import { WeaviateDB } from "../vector_stores/weaviate";
+import { OracleAIVectorSearch } from "../vector_stores/oracledb";
 
 export class EmbedderFactory {
   static create(provider: string, config: EmbeddingConfig): Embedder {
@@ -205,6 +206,8 @@ export class VectorStoreFactory {
         return new MongoDB(config as any);
       case "weaviate":
         return new WeaviateDB(config as any);
+      case "oracledb":
+        return new OracleAIVectorSearch(config as any);
       default:
         throw new Error(`Unsupported vector store provider: ${provider}`);
     }

mem0-ts/src/oss/src/vector_stores/oracledb.ts

@@ -0,0 +1,741 @@
+import type { Connection, Pool } from "oracledb";
+import { v4 as uuidv4 } from "uuid";
+import { VectorStore } from "./base";
+import { SearchFilters, VectorStoreConfig, VectorStoreResult } from "../types";
+import { loadPeer } from "../utils/load_peer";
+
+const DISTANCE_METRICS = [
+  "COSINE",
+  "EUCLIDEAN",
+  "EUCLIDEAN_SQUARED",
+  "DOT",
+  "HAMMING",
+  "MANHATTAN",
+] as const;
+
+type DistanceMetric = (typeof DISTANCE_METRICS)[number];
+type IndexType = "HNSW" | "IVF";
+
+const SCORE_FROM_DISTANCE: Record<DistanceMetric, (d: number) => number> = {
+  COSINE: (d) => Math.max(0, Math.min(1, 1 - d)),
+  EUCLIDEAN: (d) => 1 / (1 + Math.max(0, d)),
+  EUCLIDEAN_SQUARED: (d) => 1 / (1 + Math.sqrt(Math.max(0, d))),
+  HAMMING: (d) => 1 / (1 + Math.max(0, d)),
+  MANHATTAN: (d) => 1 / (1 + Math.max(0, d)),
+  DOT: (d) => -d,
+};
+
+const INDEX_PARAMETER_RANGES: Record<
+  IndexType,
+  Record<string, [number, number]>
+> = {
+  HNSW: {
+    neighbors: [2, 2048],
+    efconstruction: [1, 65535],
+  },
+  IVF: {
+    "neighbor partitions": [1, 10_000_000],
+    samples_per_partition: [1, Number.MAX_SAFE_INTEGER],
+    min_vectors_per_partition: [0, Number.MAX_SAFE_INTEGER],
+  },
+};
+
+const IDENTIFIER_RE = /^(?:"[^"]+"|[^".]+)(?:\.(?:"[^"]+"|[^".]+))*$/;
+const METADATA_KEY_RE = /^[a-zA-Z0-9_.[\],\s*]+$/;
+
+export function quoteIdentifier(name: string): string {
+  const trimmed = name.trim();
+  if (!IDENTIFIER_RE.test(trimmed)) {
+    throw new Error(`Identifier name ${name} is not valid.`);
+  }
+  return [...trimmed.matchAll(/"([^"]+)"|([^".]+)/g)]
+    .map((m) => `"${m[1] ?? m[2]}"`)
+    .join(".");
+}
+
+function jsonPath(metadataKey: string): string {
+  if (!METADATA_KEY_RE.test(metadataKey)) {
+    throw new Error(
+      `Invalid metadata key '${metadataKey}'. Only letters, numbers, underscores, ` +
+        `nesting via '.', and array wildcards '[*]' are allowed.`,
+    );
+  }
+  return metadataKey
+    .split(".")
+    .map((part) =>
+      part.endsWith("[*]") ? `."${part.slice(0, -3)}"[*]` : `."${part}"`,
+    )
+    .join("");
+}
+
+const COMPARISON_OPERATORS: Record<string, string> = {
+  eq: "==",
+  ne: "!=",
+  gt: ">",
+  gte: ">=",
+  lt: "<",
+  lte: "<=",
+};
+
+const FIELD_OPERATORS = new Set([
+  ...Object.keys(COMPARISON_OPERATORS),
+  "in",
+  "nin",
+  "contains",
+  "icontains",
+]);
+
+const LOGICAL_OPERATORS: Record<string, "and" | "or" | "not"> = {
+  $and: "and",
+  $or: "or",
+  $not: "not",
+  AND: "and",
+  OR: "or",
+  NOT: "not",
+};
+
+function isScalar(value: any): boolean {
+  return value === null || (typeof value !== "object" && !Array.isArray(value));
+}
+
+function bindFilterValue(
+  value: any,
+  binds: Record<string, any>,
+): [string, string] {
+  const name = `f_${Object.keys(binds).length}`;
+  binds[name] = value;
+  return [`$${name}`, `:${name} AS "${name}"`];
+}
+
+function jsonExists(
+  path: string,
+  predicate: string,
+  passings: string[],
+): string {
+  const passingClause =
+    passings.length > 0 ? ` PASSING ${passings.join(", ")}` : "";
+  return `JSON_EXISTS(payload, '$${path}?(${predicate})'${passingClause})`;
+}
+
+function buildFieldCondition(
+  metadataKey: string,
+  value: any,
+  binds: Record<string, any>,
+): string {
+  const path = jsonPath(metadataKey);
+
+  if (value === "*") {
+    return `JSON_EXISTS(payload, '$${path}')`;
+  }
+
+  if (isScalar(value)) {
+    if (value === null) {
+      return jsonExists(path, "@ == null", []);
+    }
+    const [variable, passing] = bindFilterValue(value, binds);
+    return jsonExists(path, `@ == ${variable}`, [passing]);
+  }
+
+  if (Array.isArray(value)) {
+    throw new Error(
+      `Oracle filter for field '${metadataKey}' must be a scalar or an operator object`,
+    );
+  }
+
+  const operators = Object.entries(value);
+  if (operators.length === 0) {
+    throw new Error(
+      `Operator filter for field '${metadataKey}' must not be empty`,
+    );
+  }
+
+  const unsupported = operators
+    .map(([op]) => op)
+    .filter((op) => !FIELD_OPERATORS.has(op));
+  if (unsupported.length > 0) {
+    throw new Error(
+      `Unsupported Oracle filter operator(s) for field '${metadataKey}': ${unsupported.sort().join(", ")}`,
+    );
+  }
+
+  const predicates: string[] = [];
+  const passings: string[] = [];
+  const additionalClauses: string[] = [];
+
+  for (const [operator, operand] of operators) {
+    if (operator in COMPARISON_OPERATORS) {
+      if (!isScalar(operand)) {
+        throw new Error(
+          `Oracle filter operator '${operator}' requires a scalar value`,
+        );
+      }
+      if (operand === null) {
+        if (operator !== "eq" && operator !== "ne") {
+          throw new Error(
+            `Oracle filter operator '${operator}' does not support null`,
+          );
+        }
+        predicates.push(`@ ${COMPARISON_OPERATORS[operator]} null`);
+        continue;
+      }
+      const [variable, passing] = bindFilterValue(operand, binds);
+      predicates.push(`@ ${COMPARISON_OPERATORS[operator]} ${variable}`);
+      passings.push(passing);
+      continue;
+    }
+
+    if (operator === "in" || operator === "nin") {
+      if (!Array.isArray(operand) || operand.length === 0) {
+        throw new Error(
+          `Oracle filter operator '${operator}' requires a non-empty array`,
+        );
+      }
+
+      const variables: string[] = [];
+      const listPassings: string[] = [];
+      for (const item of operand) {
+        if (!isScalar(item)) {
+          throw new Error(
+            `Oracle filter operator '${operator}' requires scalar values`,
+          );
+        }
+        if (item === null) {
+          variables.push("null");
+          continue;
+        }
+        const [variable, passing] = bindFilterValue(item, binds);
+        variables.push(variable);
+        listPassings.push(passing);
+      }
+
+      const membership = jsonExists(
+        path,
+        `@ in (${variables.join(", ")})`,
+        listPassings,
+      );
+      additionalClauses.push(
+        operator === "in" ? membership : `NOT (${membership})`,
+      );
+      continue;
+    }
+
+    if (typeof operand !== "string") {
+      throw new Error(
+        `Oracle filter operator '${operator}' requires a string value`,
+      );
+    }
+
+    if (operator === "contains") {
+      const [variable, passing] = bindFilterValue(operand, binds);
+      predicates.push(`@ has substring ${variable}`);
+      passings.push(passing);
+    } else {
+      const [variable, passing] = bindFilterValue(operand.toLowerCase(), binds);
+      predicates.push(`@.lower() has substring ${variable}`);
+      passings.push(passing);
+    }
+  }
+
+  const clauses = [...additionalClauses];
+  if (predicates.length > 0) {
+    clauses.unshift(jsonExists(path, predicates.join(" && "), passings));
+  }
+
+  return clauses.length === 1 ? clauses[0] : `(${clauses.join(" AND ")})`;
+}
+
+export function buildFilterGroup(
+  filters: Record<string, any>,
+  binds: Record<string, any>,
+): string {
+  const entries = Object.entries(filters ?? {});
+  if (entries.length === 0) {
+    throw new Error("Oracle filter groups must be non-empty objects");
+  }
+
+  const clauses: string[] = [];
+  for (const [key, value] of entries) {
+    const logicalOperator = LOGICAL_OPERATORS[key];
+    if (logicalOperator) {
+      if (!Array.isArray(value) || value.length === 0) {
+        throw new Error(
+          `Logical filter operator '${key}' requires a non-empty array`,
+        );
+      }
+      const nested = value.map((condition) =>
+        buildFilterGroup(condition, binds),
+      );
+      if (logicalOperator === "not") {
+        clauses.push(`NOT (${nested.join(" OR ")})`);
+      } else {
+        clauses.push(
+          `(${nested.join(logicalOperator === "and" ? " AND " : " OR ")})`,
+        );
+      }
+      continue;
+    }
+
+    if (key.startsWith("$")) {
+      throw new Error(`Unsupported Oracle logical filter operator: ${key}`);
+    }
+
+    clauses.push(buildFieldCondition(key, value, binds));
+  }
+
+  return clauses.length === 1 ? clauses[0] : `(${clauses.join(" AND ")})`;
+}
+
+export function buildWhereClause(
+  filters?: SearchFilters,
+): [string, Record<string, any>] {
+  if (!filters || Object.keys(filters).length === 0) {
+    return ["", {}];
+  }
+  const binds: Record<string, any> = {};
+  return [`WHERE ${buildFilterGroup(filters, binds)}`, binds];
+}
+
+interface OracleDBConfig extends VectorStoreConfig {
+  connectionParams?: Record<string, any>;
+  useConnectionPool?: boolean;
+  client?: Connection | Pool;
+  collectionName?: string;
+  embeddingModelDims?: number;
+  distanceMetric?: DistanceMetric;
+  doCreateIndex?: boolean;
+  indexType?: IndexType;
+  indexName?: string;
+  indexParameters?: Record<string, number>;
+  indexAccuracy?: number;
+}
+
+export class OracleAIVectorSearch implements VectorStore {
+  private readonly collectionName: string;
+  private readonly indexName: string;
+  private readonly embeddingModelDims: number;
+  private readonly distanceMetric: DistanceMetric;
+  private readonly indexType: IndexType;
+  private readonly indexParameters: Record<string, number>;
+  private readonly indexAccuracy?: number;
+  private readonly doCreateIndex: boolean;
+  private readonly config: OracleDBConfig;
+  private oracledb: any;
+  private client?: Connection | Pool;
+  private ownsClient = false;
+  private _initPromise?: Promise<void>;
+
+  constructor(config: OracleDBConfig) {
+    if (!config.connectionParams && !config.client) {
+      throw new Error(
+        "Must provide at least one of `connectionParams` and `client`",
+      );
+    }
+
+    this.collectionName = quoteIdentifier(config.collectionName || "mem0");
+    this.indexName = quoteIdentifier(
+      config.indexName || `${config.collectionName || "mem0"}_VEC_IDX`,
+    );
+
+    this.embeddingModelDims = config.embeddingModelDims ?? 1536;
+    if (
+      !Number.isInteger(this.embeddingModelDims) ||
+      this.embeddingModelDims <= 0
+    ) {
+      throw new Error("`embeddingModelDims` must be a positive integer");
+    }
+
+    const distanceMetric = (config.distanceMetric ??
+      "COSINE") as string as DistanceMetric;
+    this.distanceMetric = distanceMetric.toUpperCase() as DistanceMetric;
+    if (!DISTANCE_METRICS.includes(this.distanceMetric)) {
+      throw new Error(`Unsupported distance metric: ${config.distanceMetric}`);
+    }
+
+    const indexType = (config.indexType ?? "HNSW") as string;
+    this.indexType = indexType.toUpperCase() as IndexType;
+    if (this.indexType !== "HNSW" && this.indexType !== "IVF") {
+      throw new Error(`Unsupported index type: ${config.indexType}`);
+    }
+
+    this.indexAccuracy = config.indexAccuracy;
+    if (
+      this.indexAccuracy !== undefined &&
+      (!Number.isInteger(this.indexAccuracy) ||
+        this.indexAccuracy <= 0 ||
+        this.indexAccuracy > 100)
+    ) {
+      throw new Error("`indexAccuracy` must be an integer between 1 and 100");
+    }
+
+    this.indexParameters = this.validateIndexParameters(config.indexParameters);
+    this.doCreateIndex = config.doCreateIndex ?? true;
+    this.config = config;
+  }
+
+  private validateIndexParameters(
+    parameters?: Record<string, number>,
+  ): Record<string, number> {
+    if (!parameters) return {};
+
+    const allowed = INDEX_PARAMETER_RANGES[this.indexType];
+    const validated: Record<string, number> = {};
+
+    for (const [key, value] of Object.entries(parameters)) {
+      const range = allowed[key];
+      if (!range) {
+        throw new Error(
+          `Unsupported ${this.indexType} index parameter '${key}'. ` +
+            `Allowed: ${Object.keys(allowed).join(", ")}`,
+        );
+      }
+      if (!Number.isInteger(value) || value < range[0] || value > range[1]) {
+        throw new Error(
+          `Index parameter '${key}' must be an integer between ${range[0]} and ${range[1]}`,
+        );
+      }
+      validated[key] = value;
+    }
+
+    return validated;
+  }
+
+  async initialize(): Promise<void> {
+    if (!this._initPromise) {
+      this._initPromise = this._doInitialize();
+    }
+    return this._initPromise;
+  }
+
+  private async _doInitialize(): Promise<void> {
+    const sdk = await loadPeer(
+      "oracledb",
+      "Oracle AI Vector Search",
+      () => import("oracledb"),
+    );
+    this.oracledb = sdk.default ?? sdk;
+
+    if (this.config.client) {
+      this.client = this.config.client;
+    } else if (this.config.useConnectionPool ?? true) {
+      this.client = await this.oracledb.createPool({
+        poolMin: 1,
+        poolMax: 4,
+        ...this.config.connectionParams,
+      });
+      this.ownsClient = true;
+    } else {
+      this.client = await this.oracledb.getConnection(
+        this.config.connectionParams,
+      );
+      this.ownsClient = true;
+    }
+
+    await this.assertVectorSupport();
+    await this.createCol();
+  }
+
+  private isPool(client: Connection | Pool): client is Pool {
+    return typeof (client as Pool).getConnection === "function";
+  }
+
+  private async withConnection<T>(
+    fn: (connection: Connection) => Promise<T>,
+    commit = false,
+  ): Promise<T> {
+    const client = this.client!;
+
+    if (!this.isPool(client)) {
+      const connection = client as Connection;
+      try {
+        const result = await fn(connection);
+        if (commit) await connection.commit();
+        return result;
+      } catch (err) {
+        await connection.rollback();
+        throw err;
+      }
+    }
+
+    const connection = await client.getConnection();
+    try {
+      const result = await fn(connection);
+      if (commit) await connection.commit();
+      return result;
+    } catch (err) {
+      await connection.rollback();
+      throw err;
+    } finally {
+      await connection.close();
+    }
+  }
+
+  private async assertVectorSupport(): Promise<void> {
+    if (!this.oracledb.thin) {
+      const [major, minor] = [
+        Math.floor(this.oracledb.oracleClientVersion / 100000000),
+        Math.floor(this.oracledb.oracleClientVersion / 100000) % 100,
+      ];
+      if (major < 23 || (major === 23 && minor < 4)) {
+        throw new Error(
+          `Oracle DB client driver version ${this.oracledb.oracleClientVersionString} ` +
+            "not supported, must be >=23.4 for vector support",
+        );
+      }
+    }
+
+    const version = await this.withConnection(
+      async (connection) => connection.oracleServerVersionString,
+    );
+    const [major, minor] = version.split(".").map(Number);
+    if (major < 23 || (major === 23 && minor < 4)) {
+      throw new Error(
+        `Oracle DB version ${version} not supported, must be >=23.4 for vector support`,
+      );
+    }
+  }
+
+  private createIndexDdl(): string {
+    const accuracy = this.indexAccuracy
+      ? `WITH TARGET ACCURACY ${this.indexAccuracy}`
+      : "";
+
+    const parameterEntries = Object.entries(this.indexParameters);
+    const parameters =
+      parameterEntries.length > 0
+        ? `PARAMETERS (${[
+            `type ${this.indexType}`,
+            ...parameterEntries.map(([key, value]) => `${key} ${value}`),
+          ].join(", ")})`
+        : "";
+
+    const organization =
+      this.indexType === "HNSW"
+        ? "INMEMORY NEIGHBOR GRAPH"
+        : "NEIGHBOR PARTITIONS";
+
+    return (
+      `CREATE VECTOR INDEX IF NOT EXISTS ${this.indexName} ON ${this.collectionName} (vector) ` +
+      `ORGANIZATION ${organization} DISTANCE ${this.distanceMetric} ${accuracy} ${parameters}`
+    );
+  }
+
+  private async createCol(): Promise<void> {
+    await this.withConnection(async (connection) => {
+      await connection.execute(`
+        CREATE TABLE IF NOT EXISTS ${this.collectionName} (
+          id VARCHAR2(36) PRIMARY KEY,
+          vector VECTOR(${this.embeddingModelDims}),
+          payload JSON
+        )
+      `);
+
+      await connection.execute(`
+        CREATE TABLE IF NOT EXISTS memory_migrations (
+          id NUMBER PRIMARY KEY,
+          user_id VARCHAR2(255) NOT NULL
+        )
+      `);
+
+      if (this.doCreateIndex) {
+        await connection.execute(this.createIndexDdl());
+      }
+    }, true);
+  }
+
+  private loadPayload(value: any): Record<string, any> {
+    if (value === null || value === undefined) return {};
+    if (typeof value === "string") return JSON.parse(value);
+    if (Buffer.isBuffer(value)) return JSON.parse(value.toString("utf-8"));
+    return value;
+  }
+
+  private vectorBind(vector: number[]) {
+    return {
+      type: this.oracledb.DB_TYPE_VECTOR,
+      val: new Float32Array(vector),
+    };
+  }
+
+  private payloadBind(payload: Record<string, any>) {
+    return { type: this.oracledb.DB_TYPE_JSON, val: payload };
+  }
+
+  async insert(
+    vectors: number[][],
+    ids: string[],
+    payloads: Record<string, any>[],
+  ): Promise<void> {
+    await this.initialize();
+
+    await this.withConnection(async (connection) => {
+      for (let i = 0; i < vectors.length; i++) {
+        await connection.execute(
+          `INSERT INTO ${this.collectionName} (id, vector, payload) VALUES (:id, :vector, :payload)`,
+          {
+            id: ids[i],
+            vector: this.vectorBind(vectors[i]),
+            payload: this.payloadBind(payloads[i] ?? {}),
+          },
+        );
+      }
+    }, true);
+  }
+
+  async search(
+    query: number[],
+    topK: number = 5,
+    filters?: SearchFilters,
+  ): Promise<VectorStoreResult[]> {
+    await this.initialize();
+
+    const [whereClause, filterBinds] = buildWhereClause(filters);
+    const sql =
+      `SELECT id, payload, VECTOR_DISTANCE(vector, :query_vec, ${this.distanceMetric}) distance ` +
+      `FROM ${this.collectionName} ${whereClause} ORDER BY distance FETCH APPROX FIRST :max_rows ROWS ONLY`;
+
+    const rows = await this.withConnection(async (connection) => {
+      const result = await connection.execute<any[]>(sql, {
+        query_vec: this.vectorBind(query),
+        max_rows: topK,
+        ...filterBinds,
+      });
+      return result.rows ?? [];
+    });
+
+    return rows.map((row) => ({
+      id: row[0],
+      payload: this.loadPayload(row[1]),
+      score: SCORE_FROM_DISTANCE[this.distanceMetric](Number(row[2])),
+    }));
+  }
+
+  async get(vectorId: string): Promise<VectorStoreResult | null> {
+    await this.initialize();
+
+    const rows = await this.withConnection(async (connection) => {
+      const result = await connection.execute<any[]>(
+        `SELECT id, payload FROM ${this.collectionName} WHERE id = :vector_id`,
+        { vector_id: vectorId },
+      );
+      return result.rows ?? [];
+    });
+
+    if (rows.length === 0) return null;
+    return { id: rows[0][0], payload: this.loadPayload(rows[0][1]) };
+  }
+
+  async update(
+    vectorId: string,
+    vector: number[],
+    payload: Record<string, any>,
+  ): Promise<void> {
+    await this.initialize();
+
+    const assignments: string[] = [];
+    const binds: Record<string, any> = { vector_id: vectorId };
+
+    if (vector) {
+      assignments.push("vector = :vector");
+      binds.vector = this.vectorBind(vector);
+    }
+    if (payload) {
+      assignments.push("payload = :payload");
+      binds.payload = this.payloadBind(payload);
+    }
+    if (assignments.length === 0) return;
+
+    await this.withConnection(
+      (connection) =>
+        connection.execute(
+          `UPDATE ${this.collectionName} SET ${assignments.join(", ")} WHERE id = :vector_id`,
+          binds,
+        ),
+      true,
+    );
+  }
+
+  async delete(vectorId: string): Promise<void> {
+    await this.initialize();
+
+    await this.withConnection(
+      (connection) =>
+        connection.execute(
+          `DELETE FROM ${this.collectionName} WHERE id = :vector_id`,
+          { vector_id: vectorId },
+        ),
+      true,
+    );
+  }
+
+  async deleteCol(): Promise<void> {
+    await this.initialize();
+
+    await this.withConnection(
+      (connection) =>
+        connection.execute(`DROP TABLE ${this.collectionName} PURGE`),
+      true,
+    );
+  }
+
+  async list(
+    filters?: SearchFilters,
+    topK: number = 100,
+  ): Promise<[VectorStoreResult[], number]> {
+    await this.initialize();
+
+    const [whereClause, filterBinds] = buildWhereClause(filters);
+
+    return this.withConnection(async (connection) => {
+      const listResult = await connection.execute<any[]>(
+        `SELECT id, payload FROM ${this.collectionName} ${whereClause} FETCH FIRST :max_rows ROWS ONLY`,
+        { ...filterBinds, max_rows: topK },
+      );
+      const countResult = await connection.execute<any[]>(
+        `SELECT COUNT(*) FROM ${this.collectionName} ${whereClause}`,
+        filterBinds,
+      );
+
+      const results = (listResult.rows ?? []).map((row) => ({
+        id: row[0],
+        payload: this.loadPayload(row[1]),
+      }));
+
+      return [results, Number(countResult.rows?.[0]?.[0] ?? 0)];
+    });
+  }
+
+  async getUserId(): Promise<string> {
+    await this.initialize();
+
+    const rows = await this.withConnection(async (connection) => {
+      const result = await connection.execute<any[]>(
+        "SELECT user_id FROM memory_migrations WHERE id = 1",
+      );
+      return result.rows ?? [];
+    });
+
+    if (rows.length > 0) return rows[0][0];
+
+    const generatedUserId = uuidv4();
+    await this.setUserId(generatedUserId);
+    return generatedUserId;
+  }
+
+  async setUserId(userId: string): Promise<void> {
+    await this.initialize();
+
+    await this.withConnection(async (connection) => {
+      await connection.execute("DELETE FROM memory_migrations WHERE id = 1");
+      await connection.execute(
+        "INSERT INTO memory_migrations (id, user_id) VALUES (1, :user_id)",
+        { user_id: userId },
+      );
+    }, true);
+  }
+
+  async close(): Promise<void> {
+    if (this.client && this.ownsClient) {
+      await this.client.close();
+    }
+  }
+}

mem0-ts/src/oss/tests/oracledb.unit.test.ts

@@ -0,0 +1,328 @@
+/// <reference types="jest" />
+/** Oracle AI Vector Search filter, config and SQL tests. The driver is mocked, so no database is needed. */
+const DB_TYPE_VECTOR = { name: "DB_TYPE_VECTOR" };
+const DB_TYPE_JSON = { name: "DB_TYPE_JSON" };
+
+jest.mock("oracledb", () => ({ thin: true, DB_TYPE_VECTOR, DB_TYPE_JSON }), {
+  virtual: true,
+});
+
+import {
+  OracleAIVectorSearch,
+  buildWhereClause,
+  quoteIdentifier,
+} from "../src/vector_stores/oracledb";
+
+type Call = { sql: string; binds: any };
+
+function fakeConnection(calls: Call[], resultsBySql: Array<any[][]>) {
+  let selectIndex = 0;
+  return {
+    oracleServerVersionString: "23.4.0.24.05",
+    async execute(sql: string, binds: any = {}) {
+      calls.push({ sql: sql.replace(/\s+/g, " ").trim(), binds });
+      if (/^\s*SELECT/i.test(sql)) {
+        return { rows: resultsBySql[selectIndex++] ?? [] };
+      }
+      return { rows: [] };
+    },
+    async commit() {},
+    async rollback() {},
+    async close() {},
+  };
+}
+
+function makeStore(
+  calls: Call[],
+  results: Array<any[][]> = [],
+  overrides = {},
+) {
+  return new OracleAIVectorSearch({
+    client: fakeConnection(calls, results) as any,
+    collectionName: "mem0",
+    embeddingModelDims: 3,
+    ...overrides,
+  } as any);
+}
+
+describe("quoteIdentifier", () => {
+  it("quotes a bare name", () => {
+    expect(quoteIdentifier("mem0")).toBe('"mem0"');
+  });
+
+  it("quotes each segment of a schema-qualified name", () => {
+    expect(quoteIdentifier("app.mem0")).toBe('"app"."mem0"');
+  });
+
+  it("preserves already-quoted segments", () => {
+    expect(quoteIdentifier('"App"."Mem0"')).toBe('"App"."Mem0"');
+  });
+
+  it("rejects a name that would break out of the quoting", () => {
+    expect(() => quoteIdentifier('mem0" (x); DROP TABLE t--')).toThrow(
+      /is not valid/,
+    );
+  });
+});
+
+describe("buildWhereClause", () => {
+  it("returns no clause for empty filters", () => {
+    expect(buildWhereClause(undefined)).toEqual(["", {}]);
+    expect(buildWhereClause({})).toEqual(["", {}]);
+  });
+
+  it("binds a scalar equality instead of inlining it", () => {
+    const [clause, binds] = buildWhereClause({ user_id: "alice" });
+    expect(clause).toBe(
+      `WHERE JSON_EXISTS(payload, '$."user_id"?(@ == $f_0)' PASSING :f_0 AS "f_0")`,
+    );
+    expect(binds).toEqual({ f_0: "alice" });
+  });
+
+  it("ANDs multiple fields", () => {
+    const [clause, binds] = buildWhereClause({
+      user_id: "alice",
+      agent_id: "bot",
+    });
+    expect(clause.startsWith("WHERE (")).toBe(true);
+    expect(clause).toContain(" AND ");
+    expect(binds).toEqual({ f_0: "alice", f_1: "bot" });
+  });
+
+  it("applies every operator in a compound range filter", () => {
+    const [clause, binds] = buildWhereClause({ age: { gte: 10, lte: 20 } });
+    expect(clause).toContain("@ >= $f_0 && @ <= $f_1");
+    expect(binds).toEqual({ f_0: 10, f_1: 20 });
+  });
+
+  it("builds an existence check for the wildcard filter", () => {
+    const [clause, binds] = buildWhereClause({ user_id: "*" });
+    expect(clause).toBe(`WHERE JSON_EXISTS(payload, '$."user_id"')`);
+    expect(binds).toEqual({});
+  });
+
+  it("builds membership for in and negates it for nin", () => {
+    const [inClause] = buildWhereClause({ user_id: { in: ["a", "b"] } });
+    expect(inClause).toContain("@ in ($f_0, $f_1)");
+    expect(inClause).not.toContain("NOT (");
+
+    const [ninClause] = buildWhereClause({ user_id: { nin: ["a"] } });
+    expect(ninClause).toContain("NOT (");
+  });
+
+  it("lowercases the operand for icontains", () => {
+    const [clause, binds] = buildWhereClause({ data: { icontains: "SciFi" } });
+    expect(clause).toContain("@.lower() has substring $f_0");
+    expect(binds).toEqual({ f_0: "scifi" });
+  });
+
+  it("ORs the branches of a $or group", () => {
+    const [clause, binds] = buildWhereClause({
+      $or: [{ user_id: "alice" }, { agent_id: "bot" }],
+    });
+    expect(clause).toContain(" OR ");
+    expect(binds).toEqual({ f_0: "alice", f_1: "bot" });
+  });
+
+  it("negates a $not group", () => {
+    const [clause] = buildWhereClause({ $not: [{ user_id: "alice" }] });
+    expect(clause.startsWith("WHERE NOT (")).toBe(true);
+  });
+
+  it("nests logical groups", () => {
+    const [clause, binds] = buildWhereClause({
+      user_id: "alice",
+      $or: [{ agent_id: "bot" }, { run_id: "r1" }],
+    });
+    expect(clause).toContain(" AND ");
+    expect(clause).toContain(" OR ");
+    expect(Object.keys(binds)).toEqual(["f_0", "f_1", "f_2"]);
+  });
+
+  it("compares against JSON null without a bind", () => {
+    const [clause, binds] = buildWhereClause({ agent_id: null });
+    expect(clause).toBe(
+      `WHERE JSON_EXISTS(payload, '$."agent_id"?(@ == null)')`,
+    );
+    expect(binds).toEqual({});
+  });
+
+  it("rejects a metadata key that could escape the JSON path", () => {
+    expect(() => buildWhereClause({ 'a"?(1==1))--': "x" })).toThrow(
+      /Invalid metadata key/,
+    );
+  });
+
+  it("rejects an unsupported field operator", () => {
+    expect(() => buildWhereClause({ age: { regex: "^a" } })).toThrow(
+      /Unsupported Oracle filter operator/,
+    );
+  });
+
+  it("rejects an unsupported logical operator", () => {
+    expect(() => buildWhereClause({ $nor: [{ a: 1 }] })).toThrow(
+      /Unsupported Oracle logical filter operator/,
+    );
+  });
+
+  it("rejects an empty in list", () => {
+    expect(() => buildWhereClause({ user_id: { in: [] } })).toThrow(
+      /non-empty array/,
+    );
+  });
+
+  it("rejects a non-scalar comparison operand", () => {
+    expect(() => buildWhereClause({ age: { gt: [1] } })).toThrow(
+      /requires a scalar value/,
+    );
+  });
+});
+
+describe("OracleAIVectorSearch config validation", () => {
+  it("requires connectionParams or client", () => {
+    expect(() => new OracleAIVectorSearch({} as any)).toThrow(
+      /connectionParams.*client/,
+    );
+  });
+
+  it("rejects an unsupported distance metric", () => {
+    expect(() => makeStore([], [], { distanceMetric: "JACCARD" })).toThrow(
+      /Unsupported distance metric/,
+    );
+  });
+
+  it("rejects a non-positive embedding dimension", () => {
+    expect(() => makeStore([], [], { embeddingModelDims: 0 })).toThrow(
+      /positive integer/,
+    );
+  });
+
+  it("rejects an out-of-range index accuracy", () => {
+    expect(() => makeStore([], [], { indexAccuracy: 101 })).toThrow(
+      /between 1 and 100/,
+    );
+  });
+
+  it("rejects an index parameter that does not belong to the index type", () => {
+    expect(() =>
+      makeStore([], [], {
+        indexType: "HNSW",
+        indexParameters: { samples_per_partition: 10 },
+      }),
+    ).toThrow(/Unsupported HNSW index parameter/);
+  });
+
+  it("rejects an index parameter outside its allowed range", () => {
+    expect(() =>
+      makeStore([], [], { indexParameters: { neighbors: 1 } }),
+    ).toThrow(/between 2 and 2048/);
+  });
+});
+
+describe("OracleAIVectorSearch SQL", () => {
+  it("creates the table and a vector index on initialize", async () => {
+    const calls: Call[] = [];
+    await makeStore(calls, [], {
+      indexParameters: { neighbors: 32, efconstruction: 200 },
+      indexAccuracy: 95,
+    }).initialize();
+
+    const ddl = calls.map((c) => c.sql).join("\n");
+    expect(ddl).toContain(
+      'CREATE TABLE IF NOT EXISTS "mem0" ( id VARCHAR2(36) PRIMARY KEY, vector VECTOR(3), payload JSON )',
+    );
+    expect(ddl).toContain(
+      'CREATE VECTOR INDEX IF NOT EXISTS "mem0_VEC_IDX" ON "mem0" (vector) ORGANIZATION INMEMORY NEIGHBOR GRAPH DISTANCE COSINE WITH TARGET ACCURACY 95 PARAMETERS (type HNSW, neighbors 32, efconstruction 200)',
+    );
+  });
+
+  it("skips index creation when doCreateIndex is false", async () => {
+    const calls: Call[] = [];
+    await makeStore(calls, [], { doCreateIndex: false }).initialize();
+    expect(calls.map((c) => c.sql).join("\n")).not.toContain(
+      "CREATE VECTOR INDEX",
+    );
+  });
+
+  it("binds vectors as DB_TYPE_VECTOR and payloads as DB_TYPE_JSON on insert", async () => {
+    const calls: Call[] = [];
+    await makeStore(calls).insert([[1, 2, 3]], ["id-1"], [{ data: "hello" }]);
+
+    const insert = calls.find((c) => c.sql.startsWith("INSERT INTO"))!;
+    expect(insert.binds.id).toBe("id-1");
+    expect(insert.binds.vector.type).toBe(DB_TYPE_VECTOR);
+    expect(insert.binds.vector.val).toEqual(new Float32Array([1, 2, 3]));
+    expect(insert.binds.payload).toEqual({
+      type: DB_TYPE_JSON,
+      val: { data: "hello" },
+    });
+  });
+
+  it("converts cosine distance to a similarity score", async () => {
+    const calls: Call[] = [];
+    const store = makeStore(calls, [[["id-1", { data: "hello" }, 0.25]]]);
+    const results = await store.search([1, 2, 3], 5);
+
+    expect(results).toEqual([
+      { id: "id-1", payload: { data: "hello" }, score: 0.75 },
+    ]);
+    const select = calls.find((c) => c.sql.startsWith("SELECT id, payload,"))!;
+    expect(select.sql).toContain(
+      "VECTOR_DISTANCE(vector, :query_vec, COSINE) distance",
+    );
+    expect(select.sql).toContain("FETCH APPROX FIRST :max_rows ROWS ONLY");
+    expect(select.binds.max_rows).toBe(5);
+  });
+
+  it("inverts the sign of a DOT distance", async () => {
+    const store = makeStore([], [[["id-1", {}, -0.4]]], {
+      distanceMetric: "DOT",
+    });
+    const [result] = await store.search([1, 2, 3]);
+    expect(result.score).toBeCloseTo(0.4);
+  });
+
+  it("parses a payload returned as a JSON string", async () => {
+    const store = makeStore([], [[["id-1", '{"data":"hello"}']]]);
+    expect(await store.get("id-1")).toEqual({
+      id: "id-1",
+      payload: { data: "hello" },
+    });
+  });
+
+  it("returns null when get finds no row", async () => {
+    expect(await makeStore([], [[]]).get("missing")).toBeNull();
+  });
+
+  it("generates and persists a UUID user id when none is stored", async () => {
+    const calls: Call[] = [];
+    const userId = await makeStore(calls, [[]]).getUserId();
+
+    expect(userId).toMatch(
+      /^[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/,
+    );
+    const insert = calls.find((c) =>
+      c.sql.startsWith("INSERT INTO memory_migrations"),
+    )!;
+    expect(insert.binds).toEqual({ user_id: userId });
+  });
+
+  it("returns the stored user id when one exists", async () => {
+    expect(await makeStore([], [[["alice"]]]).getUserId()).toBe("alice");
+  });
+
+  it("returns rows and the total count from list", async () => {
+    const calls: Call[] = [];
+    const store = makeStore(calls, [[["id-1", { data: "hello" }]], [[7]]]);
+    const [results, count] = await store.list({ user_id: "alice" }, 10);
+
+    expect(results).toEqual([{ id: "id-1", payload: { data: "hello" } }]);
+    expect(count).toBe(7);
+
+    const list = calls.find((c) =>
+      c.sql.startsWith("SELECT id, payload FROM"),
+    )!;
+    expect(list.sql).toContain("WHERE JSON_EXISTS(payload,");
+    expect(list.binds).toEqual({ f_0: "alice", max_rows: 10 });
+  });
+});

mem0-ts/tsup.config.ts

@@ -44,6 +44,7 @@ const external = [
   "@elastic/elasticsearch",
   "chromadb",
   "weaviate-client",
+  "oracledb",
 ];
 
 const define = {

mem0/client/main.py

@@ -734,6 +734,7 @@ class MemoryClient:
         memory_depth: Optional[str] = None,
         usecase_setting: Optional[str] = None,
         multilingual: Optional[bool] = None,
+        agent_custom_instructions: Optional[str] = None,
     ) -> Dict[str, Any]:
         """Update the project settings.
 
@@ -744,6 +745,7 @@ class MemoryClient:
             memory_depth: Memory depth for the project.
             usecase_setting: Usecase setting for the project.
             multilingual: Whether to use the input language for memory storage and retrieval.
+            agent_custom_instructions: New extraction instructions for agent-scoped memories.
 
         Returns:
             Dictionary containing the API response.
@@ -768,6 +770,7 @@ class MemoryClient:
                     "memory_depth": memory_depth,
                     "usecase_setting": usecase_setting,
                     "multilingual": multilingual,
+                    "agent_custom_instructions": agent_custom_instructions,
                 }.items()
                 if v is not None
             },
@@ -1636,6 +1639,7 @@ class AsyncMemoryClient:
         memory_depth: Optional[str] = None,
         usecase_setting: Optional[str] = None,
         multilingual: Optional[bool] = None,
+        agent_custom_instructions: Optional[str] = None,
     ) -> Dict[str, Any]:
         """Update the project settings.
 
@@ -1646,6 +1650,7 @@ class AsyncMemoryClient:
             memory_depth: Memory depth for the project.
             usecase_setting: Usecase setting for the project.
             multilingual: Whether to use the input language for memory storage and retrieval.
+            agent_custom_instructions: New extraction instructions for agent-scoped memories.
 
         Returns:
             Dictionary containing the API response.
@@ -1670,6 +1675,7 @@ class AsyncMemoryClient:
                     "memory_depth": memory_depth,
                     "usecase_setting": usecase_setting,
                     "multilingual": multilingual,
+                    "agent_custom_instructions": agent_custom_instructions,
                 }.items()
                 if v is not None
             },

mem0/client/project.py

@@ -177,6 +177,7 @@ class BaseProject(ABC):
         self,
         custom_instructions: Optional[str] = None,
         custom_categories: Optional[List[str]] = None,
+        agent_custom_instructions: Optional[str] = None,
     ) -> Dict[str, Any]:
         """
         Update project settings.
@@ -184,6 +185,7 @@ class BaseProject(ABC):
         Args:
             custom_instructions: New instructions for the project
             custom_categories: New categories for the project
+            agent_custom_instructions: New extraction instructions for agent-scoped memories
 
         Returns:
             Dictionary containing the API response.
@@ -396,6 +398,7 @@ class Project(BaseProject):
         custom_categories: Optional[List[str]] = None,
         multilingual: Optional[bool] = None,
         decay: Optional[bool] = None,
+        agent_custom_instructions: Optional[str] = None,
     ) -> Dict[str, Any]:
         """
         Update project settings.
@@ -407,6 +410,7 @@ class Project(BaseProject):
             decay: Toggle Memory Decay for this project. When True, search-time
                 ranking boosts recently-used memories and gently dampens stale ones; when
                 False, ranking is restored to the pre-decay behaviour. Off by default.
+            agent_custom_instructions: New extraction instructions for agent-scoped memories
 
         Returns:
             Dictionary containing the API response.
@@ -418,10 +422,17 @@ class Project(BaseProject):
             NetworkError: If network connectivity issues occur.
             ValueError: If org_id or project_id are not set.
         """
-        if custom_instructions is None and custom_categories is None and multilingual is None and decay is None:
+        if (
+            custom_instructions is None
+            and custom_categories is None
+            and multilingual is None
+            and decay is None
+            and agent_custom_instructions is None
+        ):
             raise ValueError(
                 "At least one parameter must be provided for update: "
-                "custom_instructions, custom_categories, multilingual, decay"
+                "custom_instructions, custom_categories, multilingual, decay, "
+                "agent_custom_instructions"
             )
 
         payload = self._prepare_params(
@@ -430,6 +441,7 @@ class Project(BaseProject):
                 "custom_categories": custom_categories,
                 "multilingual": multilingual,
                 "decay": decay,
+                "agent_custom_instructions": agent_custom_instructions,
             }
         )
         response = self._client.patch(
@@ -445,6 +457,7 @@ class Project(BaseProject):
                 "custom_categories": custom_categories,
                 "multilingual": multilingual,
                 "decay": decay,
+                "agent_custom_instructions": agent_custom_instructions,
                 "sync_type": "sync",
             },
         )
@@ -709,6 +722,7 @@ class AsyncProject(BaseProject):
         custom_categories: Optional[List[str]] = None,
         multilingual: Optional[bool] = None,
         decay: Optional[bool] = None,
+        agent_custom_instructions: Optional[str] = None,
     ) -> Dict[str, Any]:
         """
         Update project settings.
@@ -720,6 +734,7 @@ class AsyncProject(BaseProject):
             decay: Toggle Memory Decay for this project. When True, search-time
                 ranking boosts recently-used memories and gently dampens stale ones; when
                 False, ranking is restored to the pre-decay behaviour. Off by default.
+            agent_custom_instructions: New extraction instructions for agent-scoped memories
 
         Returns:
             Dictionary containing the API response.
@@ -731,10 +746,17 @@ class AsyncProject(BaseProject):
             NetworkError: If network connectivity issues occur.
             ValueError: If org_id or project_id are not set.
         """
-        if custom_instructions is None and custom_categories is None and multilingual is None and decay is None:
+        if (
+            custom_instructions is None
+            and custom_categories is None
+            and multilingual is None
+            and decay is None
+            and agent_custom_instructions is None
+        ):
             raise ValueError(
                 "At least one parameter must be provided for update: "
-                "custom_instructions, custom_categories, multilingual, decay"
+                "custom_instructions, custom_categories, multilingual, decay, "
+                "agent_custom_instructions"
             )
 
         payload = self._prepare_params(
@@ -743,6 +765,7 @@ class AsyncProject(BaseProject):
                 "custom_categories": custom_categories,
                 "multilingual": multilingual,
                 "decay": decay,
+                "agent_custom_instructions": agent_custom_instructions,
             }
         )
         response = await self._client.patch(
@@ -758,6 +781,7 @@ class AsyncProject(BaseProject):
                 "custom_categories": custom_categories,
                 "multilingual": multilingual,
                 "decay": decay,
+                "agent_custom_instructions": agent_custom_instructions,
                 "sync_type": "async",
             },
         )

mem0/client/types.py

@@ -28,6 +28,9 @@ class AddMemoryOptions(BaseModel):
         default=None, description="Custom categories for memory classification"
     )
     custom_instructions: Optional[str] = Field(default=None, description="Custom instructions for fact extraction")
+    agent_custom_instructions: Optional[str] = Field(
+        default=None, description="Custom instructions for fact extraction from agent-scoped memories"
+    )
     timestamp: Optional[int] = Field(default=None, description="Unix timestamp for the memory")
     expiration_date: Optional[str] = Field(default=None, description="Expiration date in YYYY-MM-DD format")
     structured_data_schema: Optional[Dict[str, Any]] = Field(
@@ -107,6 +110,9 @@ class ProjectUpdateOptions(BaseModel):
     """Options for project update operations."""
 
     custom_instructions: Optional[str] = Field(default=None, description="Custom instructions for fact extraction")
+    agent_custom_instructions: Optional[str] = Field(
+        default=None, description="Custom instructions for fact extraction from agent-scoped memories"
+    )
     custom_categories: Optional[List[Dict[str, Any]]] = Field(
         default=None, description="Custom categories for classification"
     )

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0ai"
-version = "2.0.16"
+version = "2.0.17"
 description = "Long-term memory for AI Agents"
 authors = [
     { name = "Mem0", email = "support@mem0.ai" }

tests/test_client.py

@@ -440,3 +440,51 @@ class TestValidateApiKeyHttpError:
 
         assert not isinstance(exc_info.value, requests.exceptions.JSONDecodeError)
         assert "Error:" in str(exc_info.value)
+
+
+class TestAddAgentCustomInstructions:
+    """Per-request override of the project-level setting, forwarded to the add payload."""
+
+    def _mock_add(self, client):
+        response = MagicMock()
+        response.json.return_value = {"results": []}
+        response.raise_for_status.return_value = None
+        client.client.post.return_value = response
+        return response
+
+    def test_kwarg_reaches_the_add_payload(self, mock_memory_client):
+        self._mock_add(mock_memory_client)
+
+        mock_memory_client.add(
+            "hello",
+            filters={"agent_id": "a1"},
+            agent_custom_instructions="remember tool failures",
+        )
+
+        _, kwargs = mock_memory_client.client.post.call_args
+        assert kwargs["json"]["agent_custom_instructions"] == "remember tool failures"
+
+    def test_typed_option_reaches_the_add_payload(self, mock_memory_client):
+        from mem0.client.types import AddMemoryOptions
+
+        self._mock_add(mock_memory_client)
+
+        mock_memory_client.add(
+            "hello",
+            AddMemoryOptions(
+                filters={"agent_id": "a1"},
+                agent_custom_instructions="remember tool failures",
+            ),
+        )
+
+        _, kwargs = mock_memory_client.client.post.call_args
+        assert kwargs["json"]["agent_custom_instructions"] == "remember tool failures"
+
+    def test_absent_when_not_passed(self, mock_memory_client):
+        """Callers that don't use the feature send an unchanged payload."""
+        self._mock_add(mock_memory_client)
+
+        mock_memory_client.add("hello", filters={"user_id": "u1"})
+
+        _, kwargs = mock_memory_client.client.post.call_args
+        assert "agent_custom_instructions" not in kwargs["json"]

tests/test_project.py

@@ -3,8 +3,8 @@ parameter-passthrough surface.
 
 Verifies the kwarg → JSON payload mapping for every supported field
 (``custom_instructions``, ``custom_categories``, ``multilingual``,
-``decay``), the ValueError when no field is provided, and the
-URL/method shape. The HTTP layer is mocked.
+``decay``, ``agent_custom_instructions``), the ValueError when no field
+is provided, and the URL/method shape. The HTTP layer is mocked.
 """
 
 from unittest.mock import MagicMock, patch
@@ -84,6 +84,50 @@ class TestProjectUpdateDecay:
         assert args[0] == "/api/v1/orgs/organizations/org1/projects/proj1/"
 
 
+class TestProjectUpdateAgentCustomInstructions:
+    def test_agent_custom_instructions_sent_in_payload(self, project):
+        proj, http = project
+        proj.update(agent_custom_instructions="remember tool failures")
+        assert _patch_payload(http) == {"agent_custom_instructions": "remember tool failures"}
+
+    def test_agent_custom_instructions_alone_satisfies_the_guard(self, project):
+        """It is a standalone field, so setting only it must not raise."""
+        proj, http = project
+        proj.update(agent_custom_instructions="remember tool failures")
+        assert http.patch.called
+
+    def test_empty_string_round_trips_to_clear_the_field(self, project):
+        """An empty string must survive the ``is not None`` filter, not be dropped as falsy."""
+        proj, http = project
+        proj.update(agent_custom_instructions="")
+        assert _patch_payload(http) == {"agent_custom_instructions": ""}
+
+    def test_combined_with_custom_instructions(self, project):
+        """Both sets in one PATCH: the split-instruction configuration."""
+        proj, http = project
+        proj.update(
+            custom_instructions="remember user preferences",
+            agent_custom_instructions="remember tool failures",
+        )
+        assert _patch_payload(http) == {
+            "custom_instructions": "remember user preferences",
+            "agent_custom_instructions": "remember tool failures",
+        }
+
+    def test_omitted_when_none(self, project):
+        """Callers that don't pass it must send an unchanged payload."""
+        proj, http = project
+        proj.update(custom_instructions="be concise")
+        payload = _patch_payload(http)
+        assert payload == {"custom_instructions": "be concise"}
+        assert "agent_custom_instructions" not in payload
+
+    def test_no_args_raises_with_agent_instructions_in_message(self, project):
+        proj, _ = project
+        with pytest.raises(ValueError, match=r"agent_custom_instructions"):
+            proj.update()
+
+
 class TestProjectUpdateBackwardsCompat:
     def test_multilingual_only_still_works(self, project):
         """Pre-decay callers (multilingual only) keep working unchanged."""